Patent Publication Number: US-10325389-B2

Title: Editing digital notes representing physical notes

Description:
This application claims the benefit of U.S. Provisional Application No. 61/891,442, filed Oct. 16, 2013, the entire content of which is incorporated by reference herein in its entirety. 
    
    
     TECHNICAL FIELD 
     The present disclosure relates to note content capturing, recognition, extraction, and/or management tools and systems. 
     BACKGROUND 
     Paper notes have been broadly used in recording, sharing, and communicating ideas and information. For example, during a collaboration session (e.g., brainstorming session), participants write down ideas on Post-It® notes, whiteboard, or paper, and then share with one another. In addition, people commonly use notes throughout the day to memorialize information or content which the individual does not want to forget. As additional examples, people frequently use notes as reminders of actions or events to take in the future, such as to make a telephone call, revise a document or to fill out a time sheet. 
     For example, in many situations people participate in a collaboration session by writing information on paper-based notes, such as Post-It® notes. Paper Post-It® notes can readily be removed from a dispenser pad of sticky-back paper Post-It® notes and applied to various surfaces, such as whiteboards, documents, the tops of desks, telephones, or the like. Information can be written on paper Post-It® notes either before or after the paper Post-It® notes are detached from their dispenser pad or attached to their target surfaces. Paper Post-It® notes can be easily moved from one surface to another, such as between documents or between documents and the tops of desks, they can overlap edges or boundaries of documents, they can be layered, and they can be moved with the objects to which they are attached. 
     Software programs currently exist which permit computer users to generate software-based notes in digital form and to utilize the digital notes within computing environments. For example, a computer user may create digital notes and “attach” the digital notes to an electronic document, a desktop, or an electronic workspace presented by the computing environment. The computer user may manipulate the notes, allowing the notes to be created, deleted, edited, saved, and selectively viewed. The computer user may move such a note within a document, or between documents and/or the desktop, by cutting the note from a document, storing the note in a clipboard, and then pasting the note to another area of the same document or to a different document. In this way, the software programs provide a virtual representation of notes and allow an individual to utilize the digital notes in a manner similar to physical notes that he or she may use on a daily basis. 
     SUMMARY 
     In general, the disclosure describes techniques for creating and manipulating software notes representative of physical notes. 
     In one example, a method includes receiving, by one or more processors of a device, a digital note of a plurality of digital notes generated based on image data comprising a visual representation of a scene that includes a plurality of physical notes such that each of the plurality of digital notes respectively corresponds to a particular physical note of the plurality of physical notes, wherein each of the physical notes includes respective recognizable content; receiving, by the one or more processors, user input indicating a modification to one or more visual characteristics of the digital note; editing, by the one or more processors and in response to the user input, the one or more visual characteristics of the digital note; and outputting, by the one or more processors and for display, a modified version of the digital note that includes the one or more visual characteristics. 
     In another example, computing device includes a memory configured to store digital notes, and one or more processors. In this example, the one or more processors are configured to receive a digital note of a plurality of digital notes generated based on image data comprising a visual representation of a scene that includes a plurality of physical notes such that each of the plurality of digital notes respectively corresponds to a particular physical note of the plurality of physical notes, wherein each of the physical notes includes respective recognizable content; receive user input indicating a modification to one or more visual characteristics of the digital note; edit, in response to the user input, the one or more visual characteristics of the digital note; and output, for display, a modified version of the digital note that includes the one or more visual characteristics. 
     In another example, a computing system includes means for receiving a digital note of a plurality of digital notes generated based on image data comprising a visual representation of a scene that includes a plurality of physical notes such that each of the plurality of digital notes respectively corresponds to a particular physical note of the plurality of physical notes, wherein each of the physical notes includes respective recognizable content; means for receiving user input indicating a modification to one or more visual characteristics of the digital note; means for editing, in response to the user input, the one or more visual characteristics of the digital note; and means for outputting, for display, a modified version of the digital note that includes the one or more visual characteristics. 
     In another example, a computer-readable storage medium stores instructions that, when executed, cause one or more processors of a device to: receive a digital note of a plurality of digital notes generated based on image data comprising a visual representation of a scene that includes a plurality of physical notes such that each of the plurality of digital notes respectively corresponds to a particular physical note of the plurality of physical notes, wherein each of the physical notes includes respective recognizable content; receive user input indicating a modification to one or more visual characteristics of the digital note; edit, in response to the user input, the one or more visual characteristics of the digital note; and output, for display, a modified version of the digital note that includes the one or more visual characteristics. 
     The details of one or more examples of the disclosure are set forth in the accompanying drawings and the description below. Other features, objects, and advantages of the disclosure will be apparent from the description and drawings, and from the claims. 
    
    
     
       BRIEF DESCRIPTION OF DRAWINGS 
         FIG. 1  is a representation illustrating one example of a user capturing an image of a workspace with notes using an image capture device on a mobile device. 
         FIG. 2  is a block diagram illustrating one example of a mobile device. 
         FIG. 3  is a block diagram illustrating one example of a user application to process the input image. 
         FIG. 4  is a flowchart illustrating one example of a technique used to convert physical notes to digital notes and storing the digital notes in a data storage device. 
         FIG. 5  is a block diagram illustrating an example of a note recognition technique which may use multiple note recognition modules to recognize notes and extract the content of notes. 
         FIGS. 6A and 6B  are a flowchart illustrating another example of a note recognition technique. 
         FIGS. 7A-7D  are conceptual diagrams illustrating examples of notes that overlap the boundary of another note. 
         FIGS. 8A and 8B  are conceptual diagrams illustrating an example of a technique for detecting and segmenting overlapping notes based on different colors in the overlapping notes and extracting a set of content as note segments. 
         FIGS. 9A and 9B  are conceptual diagrams illustrating another example of a technique for detecting and segmenting overlapping notes based on different colors in the overlapping notes and extracting a set of content as note segments. 
         FIG. 10  is a conceptual diagram illustrating another example of a technique for detecting and segmenting overlapping notes based on different colors in the overlapping notes and extracting a set of content as note segments. 
         FIG. 11  is a conceptual diagram illustrating another example of a technique for detecting and segmenting overlapping notes based on different colors in the overlapping notes and extracting a set of content as note segments. 
         FIGS. 12A-12F and 13  are conceptual diagrams illustrating example aspects of an example technique for segmenting a plurality of overlapping notes when the notes are the same color and extracting a set of content as note segments. 
         FIG. 14  is a flowchart illustrating the example technique illustrated by  FIGS. 12A-12F and 13 . 
         FIGS. 15 and 16  illustrate an example of a marker detection toggle overlaid on an image by a graphical user interface. 
         FIGS. 17 and 18  illustrate an example of selecting and removing a digital note from one or more portions of a graphical user interface. 
         FIGS. 19 and 20  illustrate an example of selecting and adding a digital note from one portion of the graphical user interface to a second portion of the graphical user interface. 
         FIG. 21  is a flowchart illustrating an example technique for selecting, grouping, and displaying digital notes through the graphical user interface. 
         FIG. 22  is a conceptual diagram illustrating an example technique for detecting a group of digital notes, and displaying the grouped digital notes through the graphical user interface. 
         FIG. 23  is a conceptual diagram illustrating another example technique for detecting a group of digital notes, and displaying the grouped digital notes through the graphical user interface. 
         FIG. 24  is a conceptual diagram illustrating an example technique for detecting a hierarchical order of digital notes, and displaying the digital notes in order through the graphical user interface. 
         FIG. 25  is a flowchart illustrating example operations of a note management application to apply image enhancement to an input image, in accordance with one or more techniques of this disclosure. 
         FIG. 26  is a flowchart illustrating example operations of a note management application to set the background of a sub-image to a uniform color, in accordance with one or more techniques of this disclosure. 
         FIG. 27  is a conceptual diagram illustrating example operations of a note management application to set the background of a sub-image to a uniform color, in accordance with one or more techniques of this disclosure. 
         FIG. 28  is a flowchart illustrating example operations of a device to enable editing of digital notes that correspond to physical notes, in accordance with one or more techniques of this disclosure. 
         FIGS. 29A and 29B  are conceptual diagrams illustrating example operations of a device to enable editing of digital notes that correspond to physical notes, in accordance with one or more techniques of this disclosure. 
         FIG. 30  is a conceptual diagram illustrating example modification to a color of a foreground object based on an updated background color, in accordance with one or more techniques of this disclosure. 
         FIG. 31  is a flowchart illustrating example operations of a device to identify foreground regions of digital notes that correspond to physical notes, in accordance with one or more techniques of this disclosure. 
         FIGS. 32A-32B  are conceptual diagrams illustrating example masks which may be generated by a device that identifies foreground regions of digital notes that correspond to physical notes, in accordance with one or more techniques of this disclosure. 
         FIG. 33  is a conceptual diagram illustrating example operations of a device to identify foreground regions of digital notes that correspond to physical notes, in accordance with one or more techniques of this disclosure. 
         FIG. 34  is a flowchart illustrating example operations of a device to identify foreground regions of digital notes that correspond to physical notes, in accordance with one or more techniques of this disclosure. 
         FIG. 35  is a conceptual diagram illustrating example masks which may be generated by a device that identifies foreground regions of digital notes that correspond to physical notes, in accordance with one or more techniques of this disclosure. 
         FIG. 36  illustrates a plurality of digital notes enhanced in accordance with one or more techniques of this disclosure. 
         FIG. 37  is a flowchart illustrating example operations of a device to generate a plurality of digital notes that each respectively correspond to a particular physical note of a plurality of physical notes represented by an input image, in accordance with one or more techniques of this disclosure. 
         FIG. 38  is a conceptual diagram illustrating an example input image representing a plurality of physical notes which may be used by a device to generate a plurality of digital notes that each respectively correspond to a particular physical note of the plurality of physical notes, in accordance with one or more techniques of this disclosure. 
         FIG. 39  is a conceptual diagram illustrating further details of a particular physical note of the plurality of physical notes represented by the input image of  FIG. 38 , in accordance with one or more techniques of this disclosure. 
         FIGS. 40A and 40B  illustrate additional examples of digital notes extracted from an input image representing a plurality of physical notes, in accordance with one or more techniques of this disclosure. 
     
    
    
     DETAILED DESCRIPTION 
     The present disclosure describes techniques for creating and manipulating software notes representative of physical notes. For example, techniques are described for recognizing physical notes present within a physical environment, capturing information therefrom and creating corresponding digital representations of the physical notes, referred to herein as digital notes or software-based notes. Further, at least some aspects of the present disclosure are directed to techniques for managing multiple notes, such as storing, retrieving, editing the digital notes, categorizing and grouping the digital notes, or the like. 
     In general, notes can include physical notes and digital notes. Physical notes generally refer to physical objects with a general boundary and recognizable content. Physical notes can include the resulting objects after people write, draw, or enter via other type of inputs on the objects, for example, paper, white board, or other objects accepting the inputs. By way of examples, physical notes can include hand-written Post-It® notes, paper, or film, white-board with drawings, posters, and signs. In some cases, physical notes can be generated using digital techniques, e.g. printing onto printable Post-It® notes or printed document. In some cases, one object can include several physical notes. For example, several ideas can be written on separate areas of a single piece of poster paper or a white-board. In some implementations, to facilitate the recognition of these notes, marks, such as lines, shapes, colors, symbols, markers, or stickers, can be applied to the edges of the notes. Physical notes can be two-dimensional or three dimensional. Physical notes can have various shapes and sizes. For example, a physical note may be a 7.62×7.62 cm (3×3 inches) note; a physical note may be a 66.04×99.06 cm (26×39 inches) poster; and a physical note may be a triangular metal sign. In some cases, physical notes may have known shapes and/or sizes that conform to standards, such as legal, A3, A4, and other size standards, and known shapes, which may not be limited to geometric shapes, such as stars, circles, rectangles, or the like. In other cases, physical notes may have non-standardized sizes and/or irregular shapes. 
     Digital notes generally refer to digital objects with information and/or ideas. Digital notes can be generated using digital inputs. Digital inputs can include, for example, keyboards, touch screens, digital cameras, digital recording devices, stylus, digital pens, or the like. In some cases, digital notes may be representative of physical notes. 
     In some cases, digital notes may be representative of physical notes used in a collaboration space. Collaboration space generally refers to a gathering area allowing more than one person to brainstorm, such as sharing ideas and thoughts with each other. The collaboration space can also represent a virtual space allowing a group of persons to brainstorm, such as sharing ideas and thoughts remotely, besides the gathering area. The collaboration space may be referred to as workspaces, or the like. 
       FIG. 1  illustrates an example of a note recognition environment  10 . In the example of  FIG. 1 , environment  10  includes a mobile device  15  to capture and recognize one of more notes  22  from a workspace  20 . As described herein, mobile device provides an execution environment for one or more software applications that, as described, can efficiently capture and extract note content from a large number of physical notes, such as the collection of notes  22  from workspace  20 . In this example, notes  22  may be the results of a collaborative brainstorming session having multiple participants. As described, mobile device  15  and the software executing thereon may perform a variety of note-related operations, including automated creation of digital notes representative of physical notes  22  of workspace  20 . 
     In some examples, the plurality of physical notes  22  of workspace  20  may comprise notes of different color. In other examples, the plurality of physical notes  22  of workspace  20  may comprise at least one note including fiducial markings, such as markings at the upper-right and lower-left corners of the note. In other examples, the plurality of physical notes  22  of workspace  20  may comprise at least one note having one color for the body of the note and another color for the border of the note. In other examples, notes from the plurality of physical notes  22  of workspace  20  may be arranged so that they overlap, such as being arranged in a stacked overlapping relationship. In other examples, notes from the plurality of physical notes  22  of workspace  20  may be arranged adjacently. 
     In the example implementation, mobile device  15  includes, among other components, an image capture device  18 , and a presentation device  28 . In addition, although not shown in  FIG. 1 , mobile device  15  may include one or more processors, microprocessors, internal memory and/or data storage and other electronic circuitry for executing software or firmware to provide the functionality described herein. 
     In general, image capture device  18  is a camera or other component configured to capture image data representative of workspace  20  and notes  22  positioned therein. In other words, the image data captures a visual representation of an environment, such as workspace  20 , having a plurality of visual notes. Although discussed as a camera of mobile device  15 , image capture device  18  may comprise other components capable of capturing image data, such as a video recorder, an infrared camera, a CCD (Charge Coupled Device) array, a laser scanner, or the like. Moreover, the captured image data can include at least one of an image, a video, a sequence of images (i.e., multiple images taken within a time period and/or with an order), a collection of images, or the like, and the term input image is used herein to refer to the various example types of image data. 
     Presentation device  28  may include, but not limited to, an electronically addressable display, such as a liquid crystal display (LCD) or other type of display device for use with mobile device  28 . In some implementations, mobile device  15  generates the content to display on presentation device  28  for the notes in a variety of formats, for example, a list, grouped in rows and/or column, a flow diagram, or the like. Mobile device  15  may, in some cases, communicate display information for presentation by other devices, such as a tablet computer, a projector, an electronic billboard or other external device. 
     As described herein, mobile device  15 , and the software executing thereon, provide a platform for creating and manipulating digital notes representative of physical notes  22 . For example, in general, mobile device  15  is configured to process image data produced by image capture device  18  to detect and recognize at least one of physical notes  22  positioned within workspace  20 . In some examples, the mobile device  15  is configured to recognize note(s) by determining the general boundary of the note(s). After a note is recognized, mobile device  15  extracts the content of at least one of the one or more notes, where the content is the visual information of note  22 . 
     As further described below, mobile device  15  may implement techniques for automated detection and recognition of physical notes  22  and extraction of information, content or other characteristics associated with each of the physical notes. For example, mobile device  15  may allow user  26  fine grain control over techniques used by mobile device  15  to detect and recognize physical notes  22 . As one example, mobile device  15  may allow user  26  to select between marker-based detection techniques in which one or more of notes  22  includes a physical fiducial mark on the surface of the note or non-marker based techniques in which no fiducial mark is used. 
     In addition, mobile device  15  provide user  26  with an improved electronic environment for generating and manipulating corresponding digital notes representative of physical notes  22 , including removing background or other image-related artifacts from the notes. As another example, mobile device  15  may provide mechanisms allowing user  26  to easily add digital notes to and/or delete digital notes from a set of digital notes representative of the brainstorming activity associated with workspace  20 . In some example implementations, mobile device  15  provides functionality by which user  26  is able to record and manage relationships between groups of notes  22 . 
     In some example implementations, mobile device  15  provides functionality by which user  26  is able to export the digital notes to other systems, such as cloud-based repositories (e.g., cloud server  12 ) or other computing devices (e.g., computer system  14  or mobile device  16 ). 
     In the example of  FIG. 1 , mobile device  15  is illustrated as a mobile phone. However, in other examples, mobile device  15  may be a tablet computer, a personal digital assistant (PDA), a laptop computer, a media player, an e-book reader, a wearable computing device (e.g., a watch, eyewear, a glove), or any other type of mobile or non-mobile computing device suitable for performing the techniques described herein. 
       FIG. 2  illustrates a block diagram illustrating an example of a mobile device that operates in accordance with the techniques described herein. For purposes of example, the mobile device of  FIG. 2  will be described with respect to mobile device  15  of  FIG. 1   
     In this example, mobile device  15  includes various hardware components that provide core functionality for operation of the device. For example, mobile device  15  includes one or more programmable processors  70  configured to operate according to executable instructions (i.e., program code), typically stored in a computer-readable medium or data storage  68  such as static, random-access memory (SRAM) device or Flash memory device. I/O  76  may include one or more devices, such as a keyboard, camera button, power button, volume button, home button, back button, menu button, or presentation device  28  as described in  FIG. 1 . Transmitter  72  and receiver  74  provide wireless communication with other devices, such as cloud server  12 , computer system  14 , or other mobile device  16  as described in  FIG. 1 , via a wireless communication interface as described in  FIG. 1 , such as but not limited to high-frequency radio frequency (RF) signals. Mobile device  15  may include additional discrete digital logic or analog circuitry not shown in  FIG. 2 . 
     In general, operating system  64  executes on processor  70  and provides an operating environment for one or more user applications  77  (commonly referred to “apps”), including note management application  78 . User applications  77  may, for example, comprise executable program code stored in computer-readable storage device (e.g., data storage  68 ) for execution by processor  70 . As other examples, user applications  77  may comprise firmware or, in some examples, may be implemented in discrete logic. 
     In operation, mobile device  15  receives input image data and processes the input image data in accordance with the techniques described herein. For example, image capture device  18  may capture an input image of an environment having a plurality of notes, such as workspace  20  of  FIG. 1  having of notes  22 . As another example, mobile device  15  may receive image data from external sources, such as cloud server  15 , computer system  14 , or mobile device  16 , via receiver  74 . In general, mobile device  15  stores the image data in data storage  68  for access and processing by note management application  78  and/or other user applications  77 . 
     As shown in  FIG. 2 , user applications  77  may invoke kernel functions of operating system  64  to output a graphical user interface (GUI)  79  for presenting information to a user of mobile device. As further described below, note management application  78  may construct and control GUI  79  to provide an improved electronic environment for generating and manipulating corresponding digital notes representative of physical notes  22 . For example, note management application  78  may construct GUI  79  to include a mechanism that allows user  26  to easily add digital notes to and/or deleting digital notes from defined sets of digital notes recognized from the image data. In some example implementations, note management application  78  provides functionality by which user  26  is able to record and manage relationships between groups of the digital notes by way of GUI  79 . 
       FIG. 3  is a block diagram illustrating one example implementation of note management application  78  that operates in accordance with the techniques described herein. Although described as a user application  77  executing on mobile device  15 , the examples described herein may be implemented on any computing device, such as cloud server  12 , computer system  14 , or other mobile devices. 
     In this example, user application  78  includes image processing engine  82  that provides image processing and object recognition functionality. Image processing engine  82  may include image communication module  90 , note identification module  86 , digital note generation module  88 , and note enhancement module  89 . In addition, image processing engine  82  includes image processing Application Programming Interfaces (APIs)  95  that provide a library of image manipulation functions, e.g., image thresholding, masking, filtering, edge detection, and the like, for use by the other components of image processing engine  82 . 
     In general, image data may be stored in data storage device  68 . In this example, note management application  78  stores images  97  within data storage device  68 . Each of images  97  may comprise pixel data for environments having a plurality of physical images, such as workspace  20  of  FIG. 1 . 
     As described herein, note identification module  86  processes images  97  and identifies (i.e., recognizes) the plurality of physical notes in the images. The input image may be processed by note identification module  86  using marker and/or non-marker detection processes. Digital note generation module  88  generates digital notes  99  corresponding to the physical notes recognized within images  97 . For example, each of digital notes  99  corresponds to one of the physical notes identified in an input image  97 . During this process, digital note generation module  88  may update database  94  to include a record of the digital note, and may store within the database information (e.g., content) captured from boundaries of the physical note within the input image as detected by note identification module  86 . Moreover, digital note generation module  88  may store within database  94  metadata associating the digital notes into one or more groups of digital notes. 
     Note enhancement  89  enables editing and/or enhancement of digital notes, such as digital notes generated by digital note generation module  88 . For instance, note enhancement module  89  may include a process or processes that enhance the extracted information from the input image. As one example, note enhancement module  89  may include a process or processes to enhance the extracted information from the input image in accordance with the techniques of  FIGS. 26 and 27 . As another example, note enhancement module  89  may by invoked by note editor  96  to enable editing of digital notes in accordance with the techniques of  FIGS. 28-30 . Note enhancement module  89  may be configured to receive digital notes from data storage  68  and store edited digital notes to data storage  68 . In some examples, note enhancement module  89  may store an edited and/or enhanced digital note to data storage  68  by storing the digital note along with one or more objects that correspond to edits and/or enhancements of the digital note (e.g., shape layer objects of  FIG. 29 ). 
     Image communication module  90  controls communication of image data between mobile device  15  and external devices, such as cloud server  12 , computer system  14 , mobile device  16 , or image capture device  18 . In some examples, image communication modules  90  may, for example, allow a user to communicate processed or unprocessed images  97  of environments and/or digital notes and associated information extracted therefrom including metadata from database  68 . In some examples, image communication module  90  exports this data to a zip file that may be communicated by FTP, HTTP, email, Bluetooth, or other mechanism. 
     In the example of  FIG. 1 , note management application  78  includes user interface  98  that constructs and controls GUI  79  ( FIG. 2 ). As described below, user interface  98  may, in some examples, output for display an input image  97  overlaid with the plurality of digital notes  99 , where each of the digital notes is overlaid in place of a corresponding physical note. In addition, user interface  98  may display a group of digital notes  99  that has been designated by the user. This group of digital notes  99  may be, for example, a subset of the digital notes recognized in a particular input image  97 . User interface  98  may display this designated group (set) of the digital notes on a second portion of GUI  79  and allow user  26  to easily add or remove digital notes  99  from the designated group. 
     In some example implementations, user interface  98  provides a note editor  96  that allows a user to edit the overlay image and/or the digital notes. For instance, note editor  96  may allow a user to edit the digital notes in accordance with the techniques of  FIGS. 28-29A, 29B . In some examples, note editor  96  may invoke one or more components of image processing engine  82 , such as note enhancement module  89 , to perform edits on the digital notes. 
     Additional example details of note management application  78  for detecting and recognizing physical notes are described in U.S. Patent Application 61/844,140, filed Jul. 9, 2013 entitled SYSTEMS AND METHODS FOR NOTE RECOGNITION AND MANAGEMENT USING COLOR CLASSIFICATION,” U.S. Patent Application 61/844,152, filed Jul. 9, 2013, entitled “SYSTEMS AND METHODS FOR NOTE CONTENT EXTRACTION AND MANAGEMENT USING SEGMENTED NOTES, and U.S. Patent Application 61/844,176, filed Jul. 9, 2013, “SYSTEMS AND METHODS FOR NOTE CONTENT EXTRACTION AND MANAGEMENT BY SEGMENTING NOTES,” the entire contents of each of which are incorporated herein by reference. 
       FIG. 4  is a flowchart illustrating an example of a note recognition process  100  as may be implemented by note management application  78  of mobile device  15 . Initially, note identification module  86  of note management application  78  captures an input image of a plurality of notes through image acquisition ( 102 ). In some examples, the notes are physical notes and it is more efficient to capture more than one note at a time. Next, note identification module  86  recognizes one of the plurality of notes from the input image ( 104 ). For example, note identification module  86  may recognize note features using a color detection module, a shape detection module, and a pattern detection module, and subsequently determine the general boundary of the note. 
     Digital note generation module  88  extracts content of the one of the plurality of notes to create sub-images ( 106 ). In some examples, digital note generation module  88  can apply image transformation to at least part of the input image before extracting content. In some other examples, digital note generation module  88  can apply image enhancement or another image processing technique, such as removing a background of the underlying workspace or changing the color of each note in the plurality of notes, to improve the quality of the extracted content or sub-images ( 108 ). For instance, digital note generation module  88  can apply image enhancement in accordance with the techniques of  FIG. 25 . In yet other examples, digital note generation module  88  can further recognize text and figures from the extracted content or sub-images. Digital note generation module  88  stores the enhanced extracted content or sub-images to data storage  68  of mobile device  15 , and may communicate the digital notes to cloud server  12  or other computer system  14  ( 110 ). Program code or other executable instructions for causing a programmable processor to perform process  100  may be stored within a computer-readable storage of mobile device  15 . 
       FIG. 5  is a flow diagram illustrating an example of note recognition technique  120  in which note identification module  86  may use multiple detection modules to recognize notes and extract the content of notes. In some examples, the detection modules may include a color detection module, a shape detection module, and a pattern detection module. In one example, a color detection module may use color spaces such as the RGB (red, green, and blue), LAB (e.g., Hunter 1948 L,a,b color space, CIE 1976 (L*, a*, b*) color space), CMYK (cyan, magenta, yellow, and key (black)), HSV (hue, saturation, and value) etc. to identify regions of interest corresponding to the notes  125 ,  126 ,  127 ,  128  for color recognition  122 . In other examples of the shape detection module and pattern detection modules, the notes  125 ,  126 ,  127 ,  128  are further distinguished in their shape and due to the presence of unique patterns detected by shape recognition algorithm  123  (e.g., Hough transform, shape context, etc.) and pattern recognition algorithm  124  (e.g., Support Vector Machine, cross-correlation, template matching, etc.), respectively. These algorithms  122 ,  123 ,  124  may help filter out unwanted objects in the input image or other sources of the content of notes  125 ,  126 ,  127 ,  128  and leave only those regions of interest corresponding to notes  125 ,  126 ,  127 ,  128 . In another example, a computer system may be configured to execute any variation of technique  120 . In another example, a non-transitory computer-readable medium including instructions for causing a programmable processor to execute may execute any variation of technique  120 . 
       FIGS. 6A and 6B  together are a flowchart illustrating another example of a note recognition process  130 . Initially, process  130  captures an input image, such as an image of plurality of notes  22  of brainstorm session  20  through image acquisition as described in  FIGS. 1-3  ( 132 ). In some examples, the notes are physical notes and it is more efficient to capture more than one note at a time. Next, process  130  recognizes from the input image one or more notes of plurality of notes  22  as described in  FIG. 1 , which the user, such as user  26  of  FIG. 1 , may select ( 134 ). For example, process  130  can recognize note features using a color detection module, a shape detection module, and a pattern detection module, and subsequently determine the boundary of the note as described in  FIG. 5 . Next, digital note generation module  88  extracts content of each note of plurality of notes  22  to create sub-images ( 136 ). In some examples, digital note generation module  88  can apply image transformation to at least part of the input image before extracting content (not shown in  FIGS. 6A and 6B ). In some other examples, note enhancement module  89  can apply image enhancement or other image processing technique, such as removing the background from the image of the workspace or enhancing pixel data (e.g., sharpening) associated with each of the digital notes to improve the quality of the extracted content or sub-images ( 136 ). In the example of  FIG. 6B , note enhancement module  89  has, in response to user input, changed a digital note from green to white to provide increased readability ( 136 ). Program code or other executable instructions for causing a programmable processor to perform process  130  may be stored within a computer-readable storage of mobile device  15 . 
     Digital note generation module  88  may further recognize text and figures from the extracted content or sub-images (not shown in  FIGS. 6A and 6B ). Digital note generation module  88  and/or note enhancement module  89  may store the enhanced extracted content or sub-images to data storage  68  of mobile device  15 , and may subsequently communicate the original image data and/or digital notes including extracted information and metadata to cloud server  12  or computer system  14  as described in  FIGS. 1-3  ( 138 ). 
       FIGS. 7A-7D  are conceptual diagrams illustrating examples of at least one physical note that overlaps the boundary of another note.  FIG. 7A  is a conceptual diagram illustrating an example of a plurality of adjacent notes  22  of different colors on a workspace  20  that overlap, as described with respect to  FIG. 1 .  FIG. 7B  is a conceptual diagram illustrating an example of a plurality of notes  22  of one color including markings at the upper-right and lower-left corners of each note on a workspace  20  that overlap, as described with respect to  FIG. 1 .  FIG. 7C  is a conceptual diagram illustrating an example of a plurality of notes  22  in a stacked overlapping relationship, each of notes  22  having one color for the body and another color for the border, on a workspace  20  as described with respect to  FIG. 1 .  FIG. 7D  is a conceptual diagram illustrating another example of a plurality of adjacent notes  22  that overlap the boundary of another one or more of notes  22 , as described with respect to  FIG. 1 .  FIGS. 7A-7D  illustrate some examples of overlapping notes. However, notes  22  could be used in other combinations to create other examples of overlapping notes. 
     As further described below, physical notes having borders that are different in color from the body of the notes provide a form of a fiducial mark that may be used for color segmentation and detection of the physical notes. As fiducial marks, in some examples, the border color may be selected to provide good color separation from the background color, such as a white or black border color that is different from the background (body) color of the note. As further examples, the border color and the body color may be selected to be complementary colors so as to provide good color separation, such as use of cyan borders or other fiducial marks on a yellow note, thereby providing high color contrast to facilitate identification of the physical note. 
     In other examples, fiducial marks may be constructed using an invisible ink that may only be visible to the image processing engine. As another example, retro-reflective material may be used on the notes as a fiducial mark that may be responsive to a flash from the imaging device. 
       FIG. 8A  is a conceptual diagram illustrating an example technique  200  for detecting and segmenting overlapping and/or adjacent notes by using color classification algorithms. In some cases, the input image is retrieved from a visual representation (not shown in  FIG. 8A ) if the visual representation is not a single image. For example, the visual representation is a set of images, and the input image retrieved is an aggregation of at least part of the set of images. As another example, the visual representation is a video, and the input image retrieved is a combination of several or all frames of the video. 
     Upon receiving the input image as described in  FIGS. 1-3 , note management application  78  executing on mobile device  15 , cloud server  12 , or computer system  14 , identifies a plurality of overlapping physical notes by using a color detection module, which may be a component of note identification module  86 . The color detection module may convert the input image to a desirable color space (not shown in  FIG. 8A ). An example applicable color space includes, but not limited to, RGB (red, green, and blue), LAB (e.g., Hunter 1948 L,a,b color space, CIE 1976 (L*, a*, b*) color space), CMYK (cyan, magenta, yellow, and key (black)), HSV (hue, saturation, and value), HSL (hue, saturation, and lightness), HSI (hue, saturation, and intensity), sRGB (standard red, green, and blue) color space. Next, the color detection module may apply one or more classification functions to color values for each pixel in the input image (not shown in  FIG. 8A ). The classification functions can be computed using optional training steps. The classification algorithms for the color detection module can be, for example, linear discriminant analysis, quadratic classifier, Gaussian Mixture Models, Boosted Decision Trees, Support Vector Machines or the like. Using the classification algorithms, indicators indicative of color classes for each pixel in the image (not shown in  FIG. 8A ) are generated. A color class includes a particular range of wavelength or can be an “other” color class referring to any other color besides the color classes of interest. For example, a color class can be magenta, yellow, blue, orange, etc. An indicator can be represented by, for example, a number, a code, a symbol, an alphanumerical token, a color value, a grayscale value, or the like. In another example, technique  200  may also use a shape detection module and a pattern detection module as described in  FIG. 5 . 
       FIG. 8B  is a conceptual diagram illustrating an example of technique  200  where based on the indicators, the boundary of note(s)  202 B,  204 B,  206 B or note segment(s) can be determined. In one example, the adjacent pixels with a same indicator are grouped into a region and the boundary of the region can be determined. In some cases, the indicators are further processed using image processing principles, for example, noise filtering, morphological opening, or the like, before the boundary is determined. In some examples, the shape and/or the size of a note or note segment is predetermined, which can be used to determine and/or filter the general boundary of note(s)  202 B,  204 B,  206 B or note segment(s). Using the boundaries, the content of the note(s)  202 B,  204 B,  206 B or note segment(s) can be segmented and extracted to generate segmented digital notes. In another example, technique  200  may also display the input image including the plurality of segmented digital notes in place of the plurality of overlapping notes on a first portion of a graphical user interface and the plurality of digital notes on a second portion of the graphical user interface. 
       FIGS. 9A and 9B  are conceptual diagrams illustrating another example of technique  200  as technique  210  where note(s)  211 - 217  or note segment(s) overlap and have colored boundaries, borders, or colored mark(s) at one or more locations instead of having a solid color. In one example of technique  210 , a color detection module as described in  FIG. 8A  can be used to identify the boundaries, borders, or marks (as shown in  FIG. 9B ) and further extract the content of the note(s)  211 - 217  or note segment(s) (as shown in  FIG. 9A ). 
       FIG. 10  is a conceptual diagram illustrating another example of technique  200  as technique  220  where note(s)  221 - 224  or note segment(s) overlap and have colored boundaries, borders, or colored mark(s) at one or more locations instead of having solid color. In one example of technique  220 , a color detection module as described in  FIG. 8A  can be used to identify the boundaries, borders, or marks (as shown in  FIG. 10 ) and further extract the content of the note(s)  222 - 224  or note segment(s) (as shown in  FIG. 10 ). 
       FIG. 11  is a conceptual diagram illustrating another example of technique  200  as technique  230  where note(s)  231 ,  232  or note segment(s) overlap and have colored boundaries, borders, or colored mark(s) at one or more locations instead of having a solid color. In one example of technique  230 , a color detection module as described in  FIG. 8A  can be used to identify the boundaries, borders, or marks (as shown in  FIG. 11 ) and further extract the content of the note(s)  231 ,  232  or note segment(s) (as shown in  FIG. 11 ). 
     In another example, a computer system may be configured to execute any variation of techniques  200 ,  210 ,  220 ,  230 . In another example, a non-transitory computer-readable medium including instructions that cause a programmable processor to execute may execute any variation of techniques  200 ,  210 ,  220 ,  230 . 
       FIGS. 12A-12F and 13  are conceptual diagrams illustrating example aspects of an example technique  300  for segmenting a plurality of overlapping notes when the notes are the same color and extracting a set of content for the note segments, and  FIG. 14  is a flowchart illustrating example technique  300 . Upon receiving the input image as described in  FIGS. 1-3 , cloud server  12 , computer system  14 , mobile devices  15 ,  16 , and/or image processing engine  82  identifies a mass of the plurality of overlapping notes  302 A- 302 C and determines whether the overlapping notes  302 A- 302 C are the same color. 
     In  FIG. 12A  overlapping notes  302 A- 302 C are the same color and are segmented using a color detection module as described in  FIG. 8A  and as shown in  FIG. 12B  ( 320  of  FIG. 14 ). Optionally, the mass of plurality of overlapping notes  302 A- 302 C may be filled during the color detection module analysis as shown as mass  302 D in  FIG. 12C  ( 322  of  FIG. 14 ). The right-angled corners of the mass of plurality of notes  302 A- 302 C are detected using correlation templates  304 ,  306 ,  308 ,  310  ( 324  of  FIG. 14 ). The peaks  314  of the correlation templates  304 ,  306 ,  308 ,  310  are located off-center and are used to determine the corners of the mass of plurality of notes  302 A- 302 C as shown in  FIG. 12E  ( 326  of  FIG. 14 ). The corners of the mass of plurality of notes  302 A- 302 C with marks  311  applied to one or more corners along at least a part of the boundary and have corresponding correlation peaks are used to determine the correlated corners  304 A,  310 A,  310 B,  308 B,  308 C, and  306 C and the orientation of each note in the mass of plurality of notes  302 A- 302 C as shown in  FIG. 12F  ( 328  of  FIG. 14 ). In another example, the technique  300  may optionally include performing geometric correction and cropping techniques to the mass of plurality of notes  302 A- 302 C based on the orientation of each note in the mass of plurality of notes  302 A- 302 C. In another example, the marks can be a different color border, such as a white border, along the boundary of the note. In another example, technique  300  may further include determining whether at least one of the plurality of notes in the input image includes one or more marks  311  in the mass of plurality of notes  302 A- 302 C by comparing one or more marks  311  to marks in a database. 
     In  FIGS. 12A-12F  and  FIG. 13  the input image does contain one or more marks  311 , so technique  300  may include utilizing a marker detection module with the color detection module to determine the boundary of each note segment. In  FIG. 13 , based on the correlated corners  304 A,  310 A,  310 B,  308 B,  308 C, and  306 C, the boundaries of segments  312 A- 312 C of the mass can be determined ( 330  of  FIG. 14 ). In some cases, the marker detection module can determine the relative positions of marks  311 , which can be used to determine the boundaries of the plurality of note segments  312 A- 312 C. The content of note segments  312 A- 312 C of the mass can extracted from the plurality of note segments  312 A- 312 C using the determined boundaries ( 332  of  FIG. 14 ). In some cases, each piece of content is extracted from a corresponding note segment. In another example, the extracted contents of note segments  312 A- 312 C are used to generate a plurality of digital notes corresponding to the boundary of each note in the plurality of overlapping notes identified in the input image, and the plurality of digital notes include information represented by the plurality of note segments  312 A- 312 C in the input image. In another example, the extracted contents of note segments  312 A- 312 C are used to generate a plurality of segmented digital notes corresponding to the boundary of each note in the plurality of overlapping notes identified in the input image, and the plurality of segmented digital notes include information represented by the plurality of note segments  312 A- 312 C in the input image. 
       FIGS. 15 and 16  illustrate an example graphical user interface  400  presented by note management application  18 . In this example, graphical user interface  400  includes a marker detection control  402 ,  406  that selectively allows the user to enable or disable mark-based note detection modules or non-marker-based detection modules. 
     In one example, as illustrated in  FIG. 15 , a user, such as user  26  of  FIG. 1 , activates marker detection control  402  before directing note management application  18  to capture or otherwise process an input image. By activating marker detection toggle  402  to utilize a marker detection module, user  26  directs image processing engine  82  of note management application  78  to segment a plurality of detected overlapping physical notes based on fiducial markers associated with the notes. The user may activate a marker detection control  402  prior to capturing the input image of the workspace or may activate marker detection control  402  after the workspace is captured but prior to a processing of the input image to utilize a marker detection module to segment the plurality of overlapping notes based on fiducial markers. In this example, the note in the input image contains mark  404 , which can be a barcode, a color code, a color, a matrix code, a color block, a different color border, or the like. 
     In general, the marker detection module uses one or more marks  404  to determine the boundary of the note. In some cases, the note may be slanted in the input image (not shown in  FIGS. 15 and 16 ). In some other cases, the input image may be taken with geometric distortion. The marker detection module may use the determined boundary of mark  404  or a portion of mark  404  to determine the necessary image transformation and correction to the input image to obtain the content of the note. 
     In another case, as illustrated in  FIG. 16 , the user may elect to disable marker detection control  406  to not include a marker detection module in the note recognition technique. In response, image processing engine  82  of note management module  78  may invoke any one or more non-marker-based note detection algorithms such as identifying the plurality of physical notes based on shapes defined by perimeters of the plurality of notes in the input image, identifying the plurality of notes according to color spaces associated with background colors of the plurality of notes, and/or identifying the plurality of notes according to a pattern recognition algorithm. 
     For purposes of example, marker detection control  402 ,  406  is shown as a toggle UI element having an on state and an off state, although other UI elements could be used, such as radio buttons, drop down lists and the like. 
       FIGS. 17 and 18  illustrate an example in which note management application  78  of mobile device  15  provides functionality by which user  26  manages a set of digital notes associated with a workspace, such as workspace  20  of  FIG. 1 . For example, note management application  78  generates GUI  79  to include input controls that allow user  26  to selectively include or exclude notes recognized in an input image, thereby controlling which of the physical notes have corresponding digital notes in a set or group of digital notes. 
     In the example illustrated by  FIG. 17 , a mobile device includes a graphical user interface  500  with a first portion (region)  502  and a second portion (region)  504 . Note management application  78  displays within first portion  502  of graphical user interface  500  the input image captured from a workspace, where the input image typically provides a visual representation of a workspace having a plurality of physical notes. Note management application  78  displays within second portion  504  a set of digital images generated from the physical notes within the input image as recognized by note management application  78 . 
     In addition, note management application  78  may display, on the first portion  502  of graphical user interface  500 , the digital notes and enhanced sub-images associated therewith overlaid on the original input image, where each of the plurality of digital notes is presented in place of the corresponding physical note recognized by the note management application. This may, for example, aid the user in associating the digital notes with their respect physical notes in the workspace. 
     Each note in the plurality of digital notes on first portion  502  and second portion  504  of the graphical user interface may be selected  506 ,  507  by a user input for deletion from the set of digital notes. As illustrated between  FIGS. 17 and 18 , the selected digital note  506 ,  507  in the second portion of the graphical user interface may be deleted  508  from the second portion of the graphical user interface and remain in the first portion of the graphical user interface. In another example, the selected digital note  506 ,  507  may be deleted from both the first portion and the second portion of the graphical user interface. In another example, the selected digital note  506 ,  507  may be deleted from the first portion of the graphical user interface and remain in the second portion of the graphical user interface. 
       FIGS. 19 and 20  illustrate example user interfaces  510  with a first portion (region)  512  and a second portion (region)  514  presented by mobile device  15  that allow a user to select and add a digital note for inclusion within a set of digital notes created from physical notes recognized from a given workspace. As illustrated between  FIGS. 19 and 20 , digital notes  516  selected in the first portion  512  of the graphical user interface may be added to the set of digital notes  518  presented in the second portion  514  of the graphical user interface. In other words, the user may select one or more of the digital notes overlaid on the image of the workspace and indicate that the notes are to be included in a particular set of digital notes presented in the second portion of the graphical user interface. 
       FIG. 21  is a flowchart illustrating example operation of note management application  78  when, in response to user input, selecting a plurality of digital notes in the first portion of the graphical user interface or the second portion of the graphical user interface and grouping the selected plurality of digital notes. In one example of process  530 , note management application  78  executing on a computing device, mobile device  15 , cloud server  12 , or computer system  14 , as described in  FIGS. 1-3 , receives an input image ( 532 ). Next, the computing device is configured to identify a plurality of notes in the input image ( 534 ). Upon identifying the plurality of notes in the input image, the computing device generates a plurality of digital notes corresponding to the plurality of notes identified in the input image ( 536 ). After generating the plurality of digital notes, the computing device is configured to display the input image including the plurality of digital notes overlaid thereon in place of the identified plurality of notes on a first portion of graphical user interface ( 538 ). Upon displaying the first portion, the computing device is also configured to display a user-defined set of the digital notes on a second portion of the graphical user interface ( 540 ). Next, the computing device is configured to receive a user input to select at least some of the plurality of digital notes by way of the graphical user interface ( 542 ). After receiving the user input to select the plurality of digital notes, the computing device is also configured to receive a user input to group the selected plurality of digital notes to form one or more groups ( 544 ). In another example, the one or more groups may include a hierarchical order. 
       FIGS. 22-24  are conceptual diagrams illustrating examples of techniques in which note management application  78  executing on a computing device, such as mobile device  15 , detects notes and automatically groups the notes based on one or more detected grouping indicators. Upon receiving an input image as described in  FIGS. 1-3 , note management application  78  identifies a plurality of physical notes in the input image and generates a plurality of digital notes. 
     In the example technique  600  illustrated by  FIG. 22 , note management application  78  processes an input image of workspace  20  that, in this example, includes a plurality of notes separated into groups based on distance. In this example, note management application  78  identifies an indication of one or more groups based on the distances  602  between each of the recognized notes and a threshold distance as determined by mobile device  15 . That is, note management application  78  may determine clusters of physical notes within the input image and, based on the clusters, logically associate the digital notes into groups of digital notes. In some examples, note management application  78  may compute a 2D grid or 3D array of position data associated with objects within the input image and, for each recognized physical note, determine an absolute position and boundary for the note within the 2D or 3D space and thereby compute a complete representation of the workspace. Based on this information, note management application  78  can determine minimum distances between each physical note within the virtual space and, based on the distances, determine groupings of the corresponding digital notes corresponding to the physical notes. In other examples, note management application  78  may determine groupings based on a threshold value, which may be a threshold distance or a threshold ratio, pre-determined by a user or calculated by mobile device  15 . 
       FIG. 23  is a conceptual diagram illustrating another example technique  610  in which note management application  78  determines an indication of one or more groups based on loop  612  physically drawn around the plurality of notes within the workspace as detected within the input image by mobile device  15 . 
       FIG. 24  is a conceptual diagram illustrating another example technique  620  in which note management application  78  determines an indication of one or more groups based on one or more lines  622  physically drawn within the workspace so as to connect each of the physical notes and to establish a hierarchical order, as detected within the input image by mobile device  15 . In another example, the one or more loops  612  and one or more lines  622  may be a Post-It® Roll and/or Scotch® colored tapes or other material. 
     In some examples, note management application  78  may be configured to detect a template of group indicators. For example, if the user places a printed template on the wall with a known design, note management application  78  may automatically establish the location of the physical notes relative to the printed template. In one example, the template may be a calendar and the notes may represent tasks or events placed on the calendar. Upon processing an image of the workspace including the template and plurality of physical notes, note management application  78  determines the task/event as taking place on a specific date based on the location of the note within the template. Templates could either be printed and adhered to the wall, or simply projected onto the wall surface. 
     Moreover, although described by way of example to detection of physical group indicators detected within an input image, the technique may be applied to detection of one or more group indicators gestured or otherwise entered by the user upon interacting with a presence-sensitive display of mobile device or other device. 
     In some examples, techniques  600 ,  610 ,  620  may include using multiple detection modules to recognize notes and extract the content of the plurality of notes, such as a color detection module, a shape detection module, and a pattern detection module as described in  FIG. 5 . In one example of the color detection module, the technique may include using color spaces such as the RGB, HSV, CIELAB, etc. to identify regions of interest corresponding to the notes for color recognition. In other examples of the shape detection module and the pattern detection module, the notes are further distinguished in their shape and due to the presence of unique patterns detected by shape recognition (e.g., Hough transform, shape context, etc.) and pattern recognition algorithms (e.g., Support Vector Machine, cross-correlation, template matching, etc.) respectively. These algorithms help filter out unwanted objects in the input image or other sources of notes&#39; content and leave only those regions of interest corresponding to the notes. 
     In some examples, techniques  600 ,  610 ,  620  may further include a computing device, such as cloud server  12 , computer system  14 , and/or mobile devices  15 ,  16 , which are configured to gather content and group indications of the plurality of notes and display the plurality of notes according to the grouping or order of the notes  604 ,  614 ,  624 , as shown in  FIGS. 22-24 . In another example, a computer system may be configured to execute any variation of techniques  600 ,  610 ,  620 . In another example, a non-transitory computer-readable medium including instructions that cause a programmable processor to execute may execute any variation of techniques  600 ,  610 ,  620 . 
       FIG. 25  is a flowchart illustrating example operations of a note management application to apply image enhancement to an input image, in accordance with one or more techniques of this disclosure. For instance, as discussed above, in some examples, note enhancement module  89  of note management application  78  of  FIG. 3  may apply the image enhancement techniques of  FIG. 25  to one or more sub-images generated from an input image of a plurality of notes. 
     In accordance with one or more techniques of this disclosure, a device, such as mobile device  15  of  FIGS. 1 and 2 , may receive an input image ( 702 ). In some examples, one or more processors may execute an image processing engine (e.g., image processing engine  28  of  FIG. 3 ) to receive image data comprising a visual representation of a scene that includes a plurality of physical notes that each include respective recognizable content. For instance, processor  70  of mobile device  15  may execute image processing engine  82  to receive image data (e.g., as image data  722  of  FIG. 27 ) comprising a visual representation of scene that includes a plurality of physical notes that each include respective recognizable content (e.g., physical notes  724 A- 724 C of  FIG. 27 ). In some examples, the image data may be an example of an image of images  97  of  FIG. 3 . 
     As one example, image processing engine  82  may receive the image data from a camera of mobile device  15 , such as image capture device  18  of  FIGS. 1 and 2 . For instance, a user of mobile device  15 , such as user  26 , may use image capture device  18  to take a picture of a plurality of physical notes. 
     As another example, image communication module  90  of image processing engine  82  may receive the image data from one or more external devices, such as another mobile device (e.g., mobile device  16  of  FIG. 2 ), a cloud server (e.g., cloud server  12 ), a computer system (e.g., computer system  14 ), and the like. For instance, a user of another device may take a picture of a plurality of physical notes and cause the other device to send the picture to mobile device  15  (e.g., via e-mail, multimedia message, and the like). 
     As another example, image processing engine  82  may receive the image data from a storage device of mobile device  15 , such as data storage device  68 . For instance, data storage device  68  may store image data previously captured by image capture device  18  and/or image data previously received from one or more external devices. 
     In any case, image processing engine  82  may identify a plurality of notes represented by the input image ( 704 ). For instance, note identification module  86  of image processing engine  82  may recognize note features using a color detection module, a shape detection module, and a pattern detection module, and subsequently determine the general boundary of the note. In some examples, a pattern detection module can identify each of the plurality of physical notes represented in the input image using one or more pattern recognition algorithms, such as a support vector machine algorithm, a cross-correlation algorithm, and a template matching algorithm, for example. In some examples, note identification module  86  may utilize a shape detection module to identify at least one of the plurality of notes based on shapes defined by perimeters of the plurality of notes in the input image. In some examples, note identification module  86  may identify the plurality of notes according to color spaces associated with background colors the plurality of notes. In some examples, note identification module  86  may utilize a pattern detection module to identify at least one of the plurality of notes. In some examples, the pattern detection module may include pattern recognition algorithms, such as a support vector machine algorithm; a cross-correlation algorithm; and/or a template matching algorithm. In some examples, the plurality of notes in the input image may include one or more of a 7.62×7.62 centimeter (cm) (3.0×3.0 inch) note, a 66.04×99.06 cm (26.0×39.0 inch) poster, a triangular metal sign, a sticker, and a 22.59×27.94 cm (8.5×11 inch) sheet of paper. 
     Digital note generation module  88  may generate, based on the identified plurality of notes, a plurality of digital notes that each respectively correspond to a particular physical note of the plurality of physical notes ( 706 ). For instance, digital note generation module  88  may extract respective content of the plurality of identified notes to create a plurality of sub-images. As illustrated in the example of  FIG. 27 , digital note generation module  88  may extract content from physical note  724 C to create sub-image  726 . 
     Note enhancement module  89  may enhance each of the plurality of digital notes ( 708 ). In some aspects, note enhancement module  89  may enhance one or more of the digital notes by correcting shadows, lighting, rotation, and scaling of notes in the respective input image. In some examples, while the physical note to which a particular sub-image corresponds may have a uniform background color, the background of the particular sub-image may not be a uniform color (e.g., due to lighting conditions when the image data was captured, quantization errors, etc. . . . ). As such, in some examples, note enhancement module  89  may enhance the particular sub-image by setting each pixel corresponding to the background of the particular sub-image to a uniform color (e.g., pixel value). In some examples, note enhancement module  89  may set the background of the particular sub-image to a uniform color in accordance with the techniques of  FIG. 26 . In some examples, note enhancement module  89  may enhance one or more of the digital notes by correcting one or more of shadows, lighting, rotation, and/or scaling of notes in the input image. 
     In some examples, note management application  78  may enable a user to modify and/or edit the digital note. For instance, note editor  96  of user interface  98  may enable a user of mobile device  15  to edit the digital note in accordance with the techniques of  FIG. 28 . 
       FIG. 26  is a flowchart illustrating example operations of a note management application to set the background of a sub-image to a uniform color, in accordance with one or more techniques of this disclosure.  FIG. 26  is described for purposes of example with respect to  FIG. 27 .  FIG. 27  is a conceptual diagram illustrating example operations of a note management application to set the background of a sub-image to a uniform color, in accordance with one or more techniques of this disclosure. 
     As discussed above, in some examples, note enhancement module  89  of note management application  78  may apply the image enhancement techniques of  FIG. 25  to set the background of a sub-image to a uniform color. 
     As discussed above, digital note generation module  88  may identify a plurality of physical notes from image data that includes a visual representation of a scene that includes the plurality of physical notes, where each physical note includes respective recognizable content, and extract a sub-image that corresponds to a particular physical note from the image data. In some examples, the extracted sub-image may be considered to be a digital note. Digital note generation module  88  may store the plurality of digital notes to a digital data storage device, such as data storage  68  of  FIG. 3 , e.g., for retrieval by a user. In accordance with one or more techniques of this disclosure, note enhancement module  89  may identify a foreground region of the digital note ( 712 ). For instance, note enhancement module  89  may identify the foreground region as the region that includes content that corresponds to the respective recognizable content of the physical note to which the digital note corresponds. As illustrated in the example of  FIG. 27 , note enhancement module  89  may identify foreground region  728 . 
     Note enhancement module  89  may identify a background region of the digital note ( 714 ). For instance, in some examples, note enhancement module  89  may identify the background region as the parts of the digital note that are not included in the foreground region. As illustrated in the example of  FIG. 27 , note enhancement module  89  may identify background region  730 . In some examples, note enhancement module  89  may first identify background region  730 , and then identify foreground region  728  based on the identified background region  730 . In other examples, note enhancement module  89  may first identify foreground region  728 , and then identify background region  730  based on the identified foreground region  728 . In some examples, note enhancement module  89  may identify the foreground region and/or the background region of the particular digital note in accordance with the techniques of  FIG. 31 . 
     In any case, note enhancement module  89  may determine a uniform background color for the digital note ( 716 ). For instance, in some examples note enhancement module  89  may select a pixel value for the uniform background color as an average or median color value of pixels included in the background region of the digital note. 
     Note enhancement module  89  may set pixels included in the background region of the digital note to the determined uniform background color ( 718 ). As one example, note enhancement module  89  may replace pixel values of the pixels included in the background region of the digital note with a pixel value corresponding to the determined uniform background color. As another example, note enhancement module  89  may store to a data structure a bitmap mask that identifies the background region along with an indication of the determined uniform background color, such that the digital note may be rendered with the uniform background color without overwriting the original data. By setting the background of a digital note to a uniform color, note enhancement module  89  may improve the visual quality of the digital note when the digital note is rendered for display. For instance, the visual quality of enhanced digital note  732  may be greater than digital note  726 . In this way, note enhancement module  89  may improve the quality of the extracted content or sub-images. 
       FIG. 28  is a flowchart illustrating example operations of a device to enable editing of digital notes that correspond to physical notes, in accordance with one or more techniques of this disclosure.  FIG. 28  is described for purposes of example with respect to  FIGS. 29A and 29B .  FIGS. 29A and 29B  are conceptual diagrams illustrating example operations of a device to enable editing of digital notes that correspond to physical notes, in accordance with one or more techniques of this disclosure. For instance, a device that implements the techniques of  FIG. 28  may enable a user, such as user  26 , to edit or modify digital notes that correspond to physical notes. Some example edits or modification include, but are not limited to, adding/deleting typed text, adding/deleting hand-drawn text, adding/deleting drawings, modifying foreground colors, and modifying background colors. 
     Mobile device  15  may receive a digital note of a plurality of digital notes generated based on image data comprising a visual representation of a scene that includes a plurality of physical notes such that each of the plurality of digital notes respectively corresponds to a particular physical note of the plurality of physical notes, which each include respective recognizable content. For instance, as illustrated in  FIG. 29A , mobile device  15  may receive digital note  746  which corresponds to a physical note with recognizable content (i.e., a hand-written to-do list of “Buy milk” and “Wash laundry”). 
     In accordance with one or more techniques of this disclosure, a device, such as mobile device  15 , may output a digital note for display ( 740 ). For instance, the device may output an enhanced digital note generated in accordance with the techniques of  FIG. 25  and/or  FIG. 26 . As illustrated in the example of  FIG. 29A , note editor  96  of mobile device  15  may output graphical user interface (GUI)  748 A that includes digital note  746  which, as discussed above, corresponds to a physical note with recognizable content “Buy milk” and “Wash laundry.” 
     Note editor  96  may receive user input to edit the digital note ( 742 ). As one example, note editor  96  may receive an indication that a user of the device performed a gesture to “draw” a line on the digital note with a virtual pen. In some examples, the digital notes may be modified using free form writing or drawing by touching a dragging a finger on a touch screen, such as a touch screen of mobile device  15 . Alternatively, the user can perform the user input on a desktop or laptop using a mouse pointer (clicking and dragging). Note editor  96  may store data indicative of gestures created by free form writing or drawing in memory, and display an image representing the data indicative of gestures as layers overlaid on the digital note. For example, as illustrated in  FIGS. 29A and 29B , note editor  96  may store data indicative of one or more gestures (e.g., strokes) created by free from writing or drawing as objects, such as shape layer objects  759 A- 759 C. In some examples, note editor  96  may store the objects as JavaScript Object Notation (JSON) data objects, Extensible Markup Language (XML) objects, or other data objects. Since the strokes created by free form writing or drawing can be stored in memory, erasing or undoing the strokes is also possible. In some examples, note editor  96  may invoke note enhancement module  89  to perform one or more operations related to note editing. For instance, note editor  96  may invoke image enhancement module  89  to store the data indicative of the gestures. 
     As another example, note editor  96  may receive an indication that the user of the device has selected an updated background color. In some examples, as the background pixels can be tracked over time, note editor  96  may invoke note enhancement module  89  to replace the tracked background pixels with the new color (i.e., after other edits have been made to the digital note, such as edits that may cause a background pixel to become a foreground pixel). One or all of these functionalities can be provided in the form of buttons, such as touch enabled buttons included in the GUI. For instance, as illustrated in  FIGS. 29A and 29B , each of GUIs  748 B- 748 F may include text entry tool  750 , digital pen tool  752 , background color tool  754 , undo button  756 , and color selection area  758 . 
     In any case, responsive to receiving the user input, note editor  96  may output, for display, an updated version of the digital note based on the user input ( 744 ). As illustrated in the example of  FIG. 29A , responsive to receiving an indication that the user of mobile device  15  performed a gesture to draw a line on the digital note with a virtual green pen (i.e., that the user selected digital pen tool  752 , selected green selected from color selection area  758 , and performed a gesture in the shape of a checkmark), note editor  96  may output GUI  748 B that includes a green line in the shape of a checkmark. As discussed above, the stroke corresponding to the green line may be stored as a data object in a data structure, such as shape layer object  759 A. In this way, note editor  96  may enable a user to edit a digital note that corresponds to a physical note. As shown in the example of  FIGS. 29A and 29B , techniques of this disclosure enable a user to write a to-do list on a physical note, take a photo of the physical note to create a digital note corresponding to the physical note, and digitally check off items from the to-do list originally written on the physical note. 
     In some examples, note editing module  89  may determine a mask that indicates which pixels of digital note  746  are background pixels and which pixels of digital note  746  are foreground pixels. In some examples, the mask may be a bitmap with a binary value for each pixel of digital note  746  where a first binary value indicates that a particular pixel is a foreground pixel and a second binary value indicates that the particular pixel is a background pixel. 
     In some examples, when invoked by note editor  96  to edit the digital note, digital note editing module  89  may update the mask that indicates which pixels of the digital note are foreground/background pixels based on the user input. For instance, before the user input that corresponds to the green line, the mask may indicate that the pixels corresponding to the green line are background pixels. After receiving the user input that corresponds to the green line, digital note editing module  89  may update the mask such that the pixels corresponding to the green line are indicated as foreground pixels. 
     In some examples, note editor  96  may continue to receive additional user input ( 742 ) and continue to output, for display, updated versions of the digital note based on the additional user input ( 744 ). As illustrated in the example of  FIG. 29A , responsive to receiving an indication that the user of mobile device  15  performed a gesture to draw a line on the digital note with a virtual red pen (i.e., that the user selected digital pen tool  752 , selected red from color selection area  758 , and performed a gesture in the shape of a line crossing out the “Wash laundry” to-do item), note editor  96  may output GUI  748 C that includes a red line crossing out the “Wash laundry” to-do item. As discussed above, note editor  96  may store, or may invoke note enhancement module  89  to store, the stroke corresponding to the red line as an object, such as shape layer object  759 B, which may be rendered into GUI  748 C along with shape layer object  759 A and digital note  746 . In this way, the device may store the editing information separately from the digital note. 
     In some examples, digital note editing module  89  may receive user input to edit the digital note by the user typing content onto the digital note. For instance, the user may select text entry tool  750 , which may cause the device to display a virtual keyboard via which the user may enter the word “Vacuum.” As illustrated in the example of  FIG. 29B , responsive to receiving an indication that the user of mobile device  15  typed in the word “Vacuum” on the digital note with a keyboard (e.g., a virtual keyboard or physical keyboard), note editor  96  may output GUI  748 D that includes text spelling out the word “Vacuum.” In some examples, note editor  96  may provide an interface by which the user can select characteristics of the text to be typed (e.g., font, color), or may modify the characteristics of the text after typing. As discussed above, note editor  96  may store, or may invoke note enhancement module  89  to store, the text as an object, such as shape layer object  759 C, which may be rendered into GUI  748 D along with shape layer objects  759 A- 759 B, and digital note  746 . 
     In some examples, the user may desire to “undo” one or more of the edits made. For instance, in the example of  FIG. 29B , the user may desire to undo inserting the word “Vacuum.” As such, the user may select undo button  756  to undo the previously made edit. As illustrated in the example of  FIG. 29B , responsive to receiving an indication that the user of mobile device  15  performed a gesture to select undo button  756 , note editor  96  may output GUI  748 E that does not include the text spelling out the word “Vacuum.” As the text may be stored as a separate object, such as shape layer object  759 C, the device may simply render GUI  748 E without shape layer object  759 C. 
     In some examples, the user may desire to edit the digital note by changing the background color of the digital note. For instance, the user may select background color tool  754  and select a new background color from a selection of background color options displayed in background color selection area  760 . As illustrated in the example of  FIG. 29B , responsive to receiving an indication that the user of mobile device  15  has selected an updated background color, note editor  96  may update the background color of the digital note and output GUI  748 F that includes the digital note with the updated background color. For instance, note editor  96  may invoke note enhancement module  89  to update the background color of the digital note. In some examples, the updated background color may be selected from a group of colors that corresponds to colors in which the physical notes are actually available. In some examples, the updated background color may be selected from a group of colors consisting of background colors of the plurality of digital notes generated based on a single scene (e.g., a scene that includes a plurality of physical notes, one of which corresponds to the digital note currently being edited). In this way, in examples where the notes are grouped by background color, the user may move digital notes between groups with maintaining the uniformity of background colors within each group. 
     In some examples, the updated background color selected by the user may not be visually compatible with the color of one or more foreground objects (e.g., original content “Buy milk”, “Wash laundry”; and modified content such as the green check mark next to “Buy milk”, the red line crossing out “Wash laundry”, and the black text “Vacuum”). For instance, the updated background color may make one or more of the foreground objects harder to read. For example, the updated background color may decrease the contrast ratio between a particular foreground object and the background of the digital note. In accordance with one or more techniques of this disclosure, note editor  96  may automatically modify, or invoke note enhancement module  89  to automatically modify, the color of one or more foreground objects based on the updated background color. In this way, note editor  96  may enable editing of the background color of the digital note without sacrificing the readability of the one or more foreground objects. Example details of how note editor  96  may modify the color of the one or more foreground objects are discussed below with reference to  FIG. 30 . 
     In some examples, as opposed to overwriting the image data of the digital note with the edits, the device may store information corresponding to each edit as a separate data object which may be used to render the digital note. For instance, as illustrated in the example of  FIG. 29A , note editor  96  may store information corresponding to the green line in the shape of a checkmark as “shapeLayer Object [ 0 ]”  759 A. Similarly, note editor  96  may store information corresponding to the red line crossing out “Wash laundry” as “shapeLayer Object [ 1 ]”  759 B, and information corresponding to the text “Vacuum” as “shapeLayer Object [ 2 ]”  759 C. In some examples, shape layer objects  759 A- 759 C may be stored in a container along with digital note  746 . For instance, note editor  96  may store shape layer object  759 A as a set of coordinates that correspond to the location and shape of the line (i.e., the check mark), and an indication that the line is green. Similarly, note editor  96  may store digital note  746  by storing the original image data (i.e., the photograph of the physical note to which digital note  746  corresponds) along with the foreground/background mask, and an indication of a uniform background color (as discussed above with reference to  FIGS. 26 and 27 ). 
     As such, note editor  96  may enable the user to undo an edit without modifying the underlying image data of the digital note. In some examples, the rendering order may be first-in-first-out, meaning that earlier created objects are rendered “under” later created objects. 
       FIG. 30  is a conceptual diagram illustrating example modification to a color of a foreground object based on an updated background color, in accordance with one or more techniques of this disclosure. As illustrated in  FIG. 30 , a device, such as mobile device  15  of  FIGS. 1 and 2 , may receive original digital note  766 . As shown in  FIG. 30 , original digital note  766  may include foreground object  767  including the words “Electric blue” written in a dark blue on a non-uniform blue background color. As discussed above, the device may perform one or more operations to enhance original digital note  766  to generate enhanced digital note  768 . For instance, digital note editing module  89  of  FIG. 3  may enhance original digital note  766  in accordance with the techniques of  FIGS. 25-27 . As shown in  FIG. 30 , enhanced digital note  768  may include foreground object  767  (i.e., “Electric blue”) written in a dark blue on a uniform blue background color. 
     Note editor  96  may, responsive to receiving user input that indicates an updated background color, set a background color of enhanced digital note  768  to the updated background color. For instance, note editor  96  may invoke note enhancement module  89  to set the background color of enhanced digital note  768  to the updated background color. As one example, where the updated background color is purple, note editor  96  may generate colored digital note  770 A by setting the background color of enhanced digital note  768  to purple. As another example, where the updated background color is lime green, note editor  96  may generate colored digital note  770 B by setting the background color of enhanced digital note  768  to lime green. As another example, where the updated background color is orange, note editor  96  may generate colored digital note  770 C by setting the background color of enhanced digital note  768  to orange. As another example, where the updated background color is yellow, note editor  96  may generate colored digital note  770 D by setting the background color of enhanced digital note  768  to yellow. However, as discussed above, in some examples, the updated background color may not be visually compatible with the color of foreground object  767  (i.e., “Electric blue” written in a dark blue). 
     In accordance with one or more techniques of this disclosure, the device may automatically modify the color of one or more foreground objects based on the updated background color. For instance, note editor  96  may select an updated foreground color as a function of the updated background color, and set a color of one or more foreground objects to the updated foreground color. In some examples, note editor  96  may select the updated foreground color such that a contrast ratio between the updated foreground color and the updated background color is greater than a contrast ratio between a current foreground color and the updated background color. 
     In some examples, note editor  96  may select the updated foreground color based on a current foreground color and the updated background color. In some examples, note editor  96  may update the color of one or more foreground objects on a pixel-by-pixel level, e.g., may modify pixel values of each respective pixel of the foreground objects based on pixel values of the corresponding respective pixels of the foreground colors, and based on the value of the background color. For instance, the color of some pixels of foreground objects may be influenced by the previous background color. By updating the color of the pixels of the foreground objects on a pixel-by-pixel level and based on the updates and previous background colors, note editor  96  may improve the visual appearance of the digital note. 
     As one example, note editor  96  may select the updated foreground color in accordance with equations 1-15 below, where L i  is the current L value of the i th  pixel of a foreground object, a i  is the current a value of the i th  pixel of the foreground object, b i  is the current b value of the i th  pixel of the foreground object, Lnew i  is the updated L value of the i th  pixel of the foreground object, anew i  is the updated a value of the i th  pixel of the foreground object, bnew i  is the updated b value of the i th  pixel of the foreground object. 
     
       
         
           
             
               
                 
                   
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     In this example, note editor  96  can compute an updated value (Lnew i , anew i , bnew i ) of the i th  pixel of the foreground object as a function of the old value (L*, a*, b*) of the i th  pixel of the foreground object, the old note background color (L*, a*, b*), and the updated background color (L*, a*, b*). The constant “60” in the denominator of equation (9) is one example value, and other values can be chosen for the denominator. The constant value of equation (9) can be chosen to select a value that gives good visual results. For instance, using a lower value for the constant of equation (9) may cause the updated values for the pixel to retain more of the old note background color. Similarly, using a higher value for the constant of equation (9) may cause the updated values for the pixel to retain less of the old note background color. diff L , diff a , and diff b  may be thought of as representing a vector direction in which the new color is going. The updated value (Lnew i , anew i , bnew i ) reflects how the foreground color values are moved along this vector translation. 
     In some examples, note editor  96  may identify a foreground region of the digital note and a background region of the digital note, e.g., in order to modify the colors of the foreground region and the background region. As discussed above, in some examples, note editor  96  invoke note enhancement module  89  to identify the foreground region and/or the background region of a digital note in accordance with the techniques of  FIG. 31 . 
     In some examples, once the background region is identified, note editor  96  may enable editing functionality. For instance, note editor  96  may enable editing functionality on digital notes that correspond to physical notes as it will be possible to determine what the true background pixels are and the changes (i.e., edits) can be monitored as new foreground pixels.  FIG. 30  illustrates examples of changing the note color of images of physical notes. As illustrated in  FIG. 30  note editor  96  may re-color foreground pixels of colored digital notes  770 A- 770 D, e.g., to have a mix of old background color and new background color. Alternatively, note editor  96  may select the updated foreground color to be a color that is a complementary color to the updated background color based on RGB or LAB color wheel. This selection may increase the contrast. 
     As one example, note editor  96  may generate improved digital note  772 A by modifying the color of the foreground object  767  (i.e., “Electric blue”) based on the updated background color of purple to generate modified foreground object  771 A having a first modified color. As another example, note editor  96  may generate improved digital note  772 B by modifying the color of the foreground object  767  (i.e., “Electric blue”) based on the updated background color of green to generate modified foreground object  771 B having a second modified color. As another example, note editor  96  may generate improved digital note  772 C by modifying the color of the foreground object  767  (i.e., “Electric blue”) based on the updated background color of orange to generate modified foreground object  771 C having a third modified color. As another example, note editor  96  may generate improved digital note  772 D by modifying the color of the foreground object  767  (i.e., “Electric blue”) based on the updated background color of yellow to generate modified foreground object  771 D having a fourth modified color. In this way, as shown by  FIG. 30 , foreground objects  771 A- 771 D (i.e., “Electric blue”) are easier to read on improved digital notes  772 A- 772 D than on colored digital notes  770 A- 770 D, respectively. In some examples, noted editor  96  may select the first, second, third, and/or fourth modified colors based on the respective selected background color in accordance with equations (1)-(15), above. Although shown for purposes of example with the foreground objects having a uniform color throughout the object, in some examples pixel values of individual pixels of the foreground objects are modified based on the new selected background color and the original pixel value of the respective pixel. 
       FIG. 31  is a flowchart illustrating example operations of a device to identify foreground regions of digital notes that correspond to physical notes, in accordance with one or more techniques of this disclosure. For instance, a device that implements the techniques of  FIG. 31  may be able to separate foreground handwritten or hand-drawn text or drawings from note images, use color segmentation algorithms to identify contiguous segments of color different from a background color, and agglomerate the identified segments to form the foreground. 
     In accordance with one or more techniques of this disclosure, a device, such as mobile device  15  of  FIGS. 1 and 2 , may receive a digital note that corresponds to a physical note of a plurality of physical notes ( 778 ). For instance, note enhancement module  89  of  FIG. 3  may receive a digital note of a plurality of digital notes generated in accordance with the techniques of  FIG. 25  and/or  FIG. 37  (e.g., digital note editing module  89  may receive the digital note from data storage  68 ). In some examples, the digital note may be a bitmap image that corresponds to a particular physical note of the plurality of physical notes. In some examples, note enhancement module  89  may assume that the digital note has a primary note color (i.e., a background color) and one or more secondary colors used in writings and drawings on the note (i.e., foreground colors). Using this assumption, the device may apply a graph-based color segmentation algorithm ( 780 ). In some examples, the device may apply the graph-based color segmentation algorithm described in “ Efficient Graph - Based Image Segmentation ,” Felzenszwalb and Huttenlocher, International Journal of Computer Vision, Volume 59, Number 2, September 2004 available at http://www.cs.cornell.edu/˜dph/papers/seg-ijcv.pdf, the entirety of which is hereby incorporated by reference. In some examples, the color segmentation algorithm may generate multiple contiguous segments based on color and proximity of pixels. It is possible to get multiple segments on the same foreground or background color because of color changes induced by shadow, lighting changes, etc. In some examples, note enhancement module  89  may fuse these segments together based on a size threshold. 
     The device may identify the foreground regions of the digital note ( 782 ). For instance, note enhancement module  89  may perform a logical OR operation to all of the individual foreground segments to generate a foreground mask. Some example resulting masks are shown in  FIGS. 32A-32B . For instance, as illustrated in  FIG. 32A , note enhancement module  89  may generate foreground mask  786  based on digital note  788 . Such a foreground mask can be used to separate the writing/drawing from the background color. This can enable variable enhancement options for foreground and background, e.g., for visually pleasing notes. Additionally, as discussed above, note enhancement module  89  may digitally change the background color of the note after a physical note was captured. 
       FIG. 33  is a conceptual diagram illustrating example operations of a device to identify foreground regions of digital notes that correspond to physical notes, in accordance with one or more techniques of this disclosure. For instance, a device that implements the techniques of  FIG. 31  may generate a mask that indicates which pixels of a digital note are included in the foreground region and which pixels of the digital note are included in the background region. 
     In accordance with one or more techniques of this disclosure, a device, such as mobile device  15  of  FIGS. 1 and 2 , may implement a hierarchical adaptive thresholding algorithm to extract binary masks of images of notes to separate the foreground from the background while providing low false positives (artifacts). This algorithm can also be generalized to other images where there is a foreground present in noisy but uniform background. 
     In some examples, the device may use dynamic scale selection. For instance, as opposed to pre-computing the adaptive threshold masks in all scales, the device may compute the scales specifically for each connected component dynamically as necessary. In addition, in some examples, the device may integrate hypotheses for shadow in the background pixel relabeling steps (i.e., steps  826 - 830  of  FIG. 34 ). 
     Various approaches may be used for enhancing images to improve their aesthetics and to remove undesirable effects such as shadows, noise, etc. . . . Among these, binarization is an approach for creating layers of foreground and background in images to obtain high levels of contrast. Usually binarization is performed to extract an object of interest and provide it more contrast with respect to its background. Such binarization can be thought of as direct foreground detection agnostic to its visual characteristics as long as the background exhibits uniformity in color. In some examples, binarization may be used to extract ventricular regions from cineangiograms (e.g., Chow, C. K., and T. Kaneko, “Automatic boundary detection of the left ventricle from cineangiograms,” Computers and biomedical research 5.4 (1972): 388-410). For instance, local windows across the image may be used to compute intensity histograms and compute thresholds dynamically. Pixels beyond these computed thresholds may be binarized as foreground. Simpler alternatives may be derived which replace computing full intensity histograms with computing approximate measures such as the mean, median, or average of the maximum and minimum values in the window. Such methods have also been used for document binarization (see, e.g., Sauvola, Jaakko, and Matti Pietikäinen. “Adaptive document image binarization.” Pattern Recognition 33.2 (2000): 225-236), the entirety of which is hereby incorporated by reference. Integral image based computing methods may improve efficiency of the thresholding process (see, e.g., Shafait, Faisal, Daniel Keysers, and Thomas M. Breuel. “Efficient implementation of local adaptive thresholding techniques using integral images.” DRR 6815 (2008): 681510). An extensive survey comparing image thresholding techniques is provided in Sezgin M, Sankur B; “Survey over image thresholding techniques and quantitative performance evaluation”. J. Electron. Imaging. 0001; 13(1):146-168, the entirety of which is hereby incorporated by reference. 
     In accordance with one or more techniques of this disclosure, note enhancement module  89  may use a hierarchical adaptive thresholding approach to enhance images of notes (e.g., digital notes that correspond to physical notes). In some examples, digital notes may have a uniform background color along with foreground content created often using different types of writing instruments. As such, digital notes may comply with the requirements for achieving good binarization results. However, direct application of adaptive thresholding for binarizing the digital note into foreground and background may not often produce desirable results. For example, as illustrated in  FIG. 33 , digital note  804  may be an example result of obtaining a binarization using adaptive thresholding of original digital note  802 . In the example of  FIG. 33 , the device may use a window size of 21×21 pixels for adaptive thresholding an image size of 500×500 pixels (i.e., original digital note  802  is 500 pixels wide by 500 pixels tall). For other image sizes, the window size may be scaled accordingly. In some examples, the window size may be linearly scaled. In some examples, the window size may be non-linearly scaled. 
     This particular window size (i.e., 21×21 for an image size of 500×500 pixels) may result in very clean backgrounds with low false positives (background wrongly predicted as foreground). However, the particular window size may result in high false negatives (foreground wrongly predicted as background). In some examples, the device may decrease the number of high false negatives by increasing the window size for the adaptive thresholding process. For instance, digital note  806  may be an example result of obtaining a binarization using adaptive thresholding of original digital note  802  using a larger window size than the window size used to generate digital note  804 . 
     As shown in digital note  806 , the foreground objects are fully extracted. However, digital note  806  also includes multiple artifacts that are inaccurately extracted as foreground. In this process, a device may perform a contrast stretch operation with the determination of the foreground and background. The background may have increased brightness (V in the HSV color space) and the foreground may have decreased brightness. This operation may make the artifacts look worse. In order to remedy this, the device may perform a hierarchical search on multiple scales of adaptive thresholding. For instance, the device may perform a hierarchical search on multiple scales of adaptive thresholding in accordance with the techniques of  FIG. 34 . 
       FIG. 34  is a flowchart illustrating example operations of a device to identify foreground regions of digital notes that correspond to physical notes, in accordance with one or more techniques of this disclosure. As illustrated in  FIG. 34 , the device may perform a hierarchical search on multiple scales of adaptive thresholding in accordance with the following steps: 
     Step  1 : The device may produce the adaptive threshold masks across various scales starting from native scale s and in octaves: s/2, s/4, s/8 etc. ( 810 ). 
     Step  2 : The device may use the native scale s as the seed of the hierarchical search ( 812 ). In some examples, foreground objects missed in the native scale cannot be retrieved in lower scales. However, for solid foreground objects, the contour obtained in native scale can be used as a seed for searching in lower scales in some examples. In this step, the device may perform a connected components extraction on the mask obtained at native scale ( 814 ): 
     Step  3 : For each connected component, the device may extract the bounding box ( 816 ). 
     Step  4 : The device may sample background pixels surrounding the bounding box ( 818 ). In some examples, the device may use 10% of the bounding box width/height to define a local background neighborhood that defines which pixels are sampled in step  818 . In some examples, the device may only use pixels identified in the original mask as background pixels (i.e., pixels in the original mask that correspond to 0) as these are the background pixels. 
     Step  5 : The device may compute the average local background color (i.e., using the sampling from Step  4  ( 820 ). In some examples, the pixels are represented by the LAB color space and the device may only use the a and b components to compute the average local background color. In some examples, the pixels are represented by an alternate chroma color space. 
     Step  6 : The device may compute the average of the foreground pixels in the current connected component ( 822 ) 
     Step  7 : The device may take each background pixel in the current connected component and compare the a and b values to the background average computed in Step  5  and the foreground average computed in step  6  ( 824 ). If the value is closer to the foreground value than background value ( 826 ) and the pixel is a foreground pixel in the mask at scale s_current/2, (where s_current is the current scale) ( 828 ) then assign the current pixel to the foreground ( 830 ). 
     Step  8 : The device may determine the amount of change in the mask of each connected component. If the amount of change is greater than a certain threshold (e.g. 70%) ( 832 ), the device may repeat Steps  3  to  7  at lower scales until the change is less than the threshold ( 834 ) ( 836 ). 
     This process results in a hierarchically modified mask. One example of the change in the mask across different scales, for digital note  802  of  FIG. 33 , is illustrated in  FIG. 35 . As illustrated by  FIG. 35 , mask  840  may represent a mask for digital note  802  at a first scale (which may be the native scale), mask  842  may represent a mask for digital note  802  at a second scale, mask  844  may represent a mask for digital note  802  at a third scale, and mask  846  may represent a mask for digital note  802  at a fourth scale. 
       FIG. 36  illustrates a plurality of digital notes processed in accordance with one or more techniques of this disclosure. As illustrated in  FIG. 36 , digital notes  850 A and  850 B (collectively, “digital notes  850 ”) may be processed into enhanced digital notes  852 A and  852 B (collectively, “enhanced digital notes  852 ”). For instance, a device may identify foreground regions in each of digital notes  850 , and set pixels not included in the foreground regions (i.e., pixels included in background regions) to a uniform background pixel color. In some examples, the device may identify the foreground regions in accordance with the techniques of  FIGS. 31-35 . In some examples, the device may set the pixels not included in the identified foreground regions to a uniform background color in accordance with the techniques of  FIGS. 25-27 . As shown in  FIG. 36 , when performing the processing, the device may stretch the contrast between the foreground and background pixels by making the background brighter and the foreground darker. 
       FIG. 37  is a flowchart illustrating example operations of a device to generate a plurality of digital notes that each respectively correspond to a particular physical note of a plurality of physical notes represented by an input image, in accordance with one or more techniques of this disclosure. 
     In accordance with one or more techniques of this disclosure, a device, such as mobile device  15  of  FIGS. 1 and 2 , may receive an input image ( 902 ). In some examples, one or more processors of the device may execute an image processing engine (e.g., image processing engine  28  of  FIG. 3 ) to receive image data comprising a visual representation of a scene that includes a plurality of physical notes that each include respective recognizable content. For instance, processor  70  of mobile device  15  may execute image processing engine  82  to receive image data (e.g., as image data  918  of  FIG. 38 ) comprising a visual representation of scene that includes a plurality of physical notes that each include respective recognizable content (e.g., notes  920 A- 920 C of  FIG. 38 ). In some examples, image data  918  may be an example of an image of images  97  of  FIG. 3 . In some examples, operation  902  may be an example of operation  702  of  FIG. 25 . 
     In any case, the device may perform pixel wise color classification ( 904 ). For instance, the device may execute one or more color classification algorithms (e.g., based on Linear/Non-Linear Discriminant Analysis) to detect and distinguish different colored regions in the input image. 
     The device may perform morphological processing ( 906 ) and extract connected components ( 908 ). For instance, the device may perform morphological processing to remove regions that do not conform to one or more constraints (e.g., shapes, ratios, sizes, etc.). As one example, the device may remove regions that are non-rectangular. 
     In some examples, each of the physical notes represented by the input image may have a plurality of differently colored regions. For instance, as illustrated in  FIG. 38 , each of notes  920 A- 920 C may include a first colored region  922 A- 922 C (collectively, “first colored regions  922 ” or yellow regions), respectively, and a second colored region  924 A- 924 C (collectively, “second colored regions  924 ” or blue regions), respectively. In some examples, the input image may include one or more regions that are not associated with any of the notes. For instance, as illustrated in  FIG. 38 , input image  918  may include region  926  which is not associated with any of notes  920 . However, as illustrated in  FIG. 38 , region  926  may be similar to a region of second colored regions  924 . 
     In accordance with one or more techniques of this disclosure, the device may exploit the fact that the notes include a plurality of differently colored regions to improve the accuracy at which the notes may be identified/recognized. For instance, the device may perform color pair matching (to, e.g., pair the regions) ( 910 ). As one example, the device may execute a Hungarian Algorithm to perform the color pair matching based on the assumption that each note includes a single first colored region and a single second colored region. For instance, when executing the Hungarian Algorithm, the device may verify if the distance between a first colored region (e.g., first colored regions  922  of  FIG. 38 ) and a second colored region (e.g., second colored regions  924  of  FIG. 38 ) is the shortest among all possible distances between that first/second colored region with other first/second colored regions. In some examples, if the distances are shortest mutually, the device may consider the regions to be a pair. Also, the device may not assign outliers, such as region  926  of  FIG. 38 , to any pair. This may be a natural consequence of the Hungarian Algorithm. The device may pair the first colored region closest to the outlier (i.e., first colored region  922 C) with the outlier (e.g., outlier  926 ) because there exists another second colored region which is closer to the first colored region. 
     If the device achieves color pairing, the device may extract digital notes from the input image ( 912 ). For instance, the device may extract a digital note for each pair of regions. As illustrated in  FIG. 38 , the device may extract a digital note for each note of notes  920 . 
     In some examples, the device may perform rotation and/or inversion adjustment on the extracted digital notes ( 914 ). In some examples, the device may determine an orientation of the note based on a line that joins features (e.g., centroids) of a pair of regions. For instance, the device may determine an angle formed by the line and a Y-axis of the digital note, and rotate the digital note based on the determined angle to compensate. As illustrated in the example of  FIG. 39 , the device may determine line  936  that joins centroid  930  of first colored region  922 B with centroid  932  of second colored region  924 B of note  920 B. The device may determine angle α  934  formed by line  936  and Y-axis  938 . Based on angle α  934 , the device may rotate digital note  920 B. For instance, if angle α  934  is 20 degrees, the device may rotate digital note  920 B counter-clockwise 20 degrees. 
       FIGS. 40A and 40B  illustrate additional examples of note extraction. As illustrated by  FIG. 40A , a device may extract digital notes  944 A- 944 E (collectively, “digital notes  944 ”) from input image  942 . As illustrated by digital notes  944 , the device may perform rotation and/or inversion adjustment to compensate for the orientation of the physical notes as represented in input image  942 . Similarly, as illustrated by  FIG. 40B , a device may extract digital notes  950 A- 950 F (collectively, “digital notes  950 ”) from input image  948 . As illustrated by digital notes  950 , the device may perform rotation and/or inversion adjustment to compensate for the orientation of the physical notes as represented in input image  942 . 
     The following numbered examples may illustrate one or more aspects of the disclosure: 
     Example 1 
     A method comprising: receiving, by one or more processors of a device, a digital note of a plurality of digital notes generated based on image data comprising a visual representation of a scene that includes a plurality of physical notes such that each of the plurality of digital notes respectively corresponds to a particular physical note of the plurality of physical notes, wherein each of the physical notes includes respective recognizable content; receiving, by the one or more processors, user input indicating a modification to one or more visual characteristics of the digital note; editing, by the one or more processors and in response to the user input, the one or more visual characteristics of the digital note; and outputting, by the one or more processors and for display, a modified version of the digital note that includes the one or more visual characteristics. 
     Example 2 
     The method of example 1, wherein: receiving the user input comprises receiving user input that indicates additional content for the digital note, editing the one or more visual characteristics of the digital note comprises creating a layer object that includes the additional content, and outputting the modified updated version of the digital note comprises outputting the modified version of the digital note such that the layer object that includes the additional content is displayed on top of content corresponding to the respective recognizable content of the physical note to which the digital note corresponds. 
     Example 3 
     The method of any combination of examples 1-2, wherein the additional content is first additional content, the layer object is a first layer object of a plurality of layer objects, and the modified version of the digital note is a first modified version of the digital note, the method further comprising: responsive to receiving user input indicating second additional content: creating a second layer of the plurality of layer objects that includes the second additional content; and outputting, for display, a second modified version of the digital note such that the second layer object that includes the second additional content is displayed on top of the first layer object that includes the first additional content. 
     Example 4 
     The method of any combination of examples 1-3, further comprising: responsive to receiving user input to remove the second layer object from the updated version of the digital note, outputting, for display, a third modified version of the digital note such that the second additional content included in the second layer object is not displayed. 
     Example 5 
     The method of any combination of examples 1-4, wherein receiving the user input that indicates the additional content comprises receiving one or more of: a sequence of typed characters, and a stroke gesture. 
     Example 6 
     The method of any combination of examples 1-5, wherein: receiving the user input comprises receiving user input that indicates an updated background color, editing the one or more visual characteristics of the digital note comprises setting a background color of the digital note to the updated background color. 
     Example 7 
     The method of any combination of examples 1-6, further comprising: identifying, for the digital note, a foreground region that includes content corresponding to recognizable content of the physical note to which the digital note corresponds, wherein at least a portion of the content of the foreground region is associated a foreground color; and modifying the foreground color. 
     Example 8 
     The method of any combination of examples 1-7, wherein: receiving the user input comprises receiving user input that indicates an updated foreground color, and modifying the foreground color comprises setting the foreground color to the updated foreground color in response to receiving user input that indicates the updated foreground color. 
     Example 9 
     The method of any combination of examples 1-8, wherein modifying the foreground color comprises automatically modifying the foreground color as a function of the updated background color. 
     Example 10 
     The method of any combination of examples 1-9, wherein prior to modifying the foreground color, a plurality of pixels included in the foreground region have current foreground pixel colors, and wherein modifying the foreground color comprises modifying colors of the plurality of pixels included in the foreground region by at least: selecting, by the one or more processors and for each pixel of the plurality of pixels included in the foreground region, an updated foreground pixel color such that a contrast ratio between the updated foreground pixel color and the updated background color is greater than a contrast ratio between the current foreground pixel color and the updated background color, and setting each respective pixel of the plurality of pixels to the selected respective updated foreground pixel color. 
     Example 11 
     The method of any combination of examples 1-10, further comprising: identifying, subsequent to identifying the foreground region of the digital note, a background region of the digital note by at least identifying pixels of the digital note not included in the foreground region as the background region. 
     Example 12 
     The method of any combination of examples 1-10, further comprising: identifying a background region of the digital note by at least identifying pixels of the digital note not included in the foreground region as the background region, wherein identifying the foreground region is performed subsequent to identifying the background region, and wherein identifying the foreground region for the particular digital note comprises: identifying pixels of the particular digital note not included in the background region as the foreground region. 
     Example 13 
     The method of any combination of examples 1-12, wherein receiving the digital note of the plurality of digital notes comprises: receiving, by the one or more processors and from a camera of the device, the image data comprising the visual representation of the scene that includes the plurality of physical notes; and generating, by the one or more processors and based on the image data, the plurality of digital notes that each respectively correspond to the particular physical note of the plurality of physical notes. 
     Example 14 
     The method of any combination of examples 1-13, further comprising: enhancing, by the one or more processors, the digital note of the plurality of digital notes by at least: identifying, for the digital note, a foreground region that includes content corresponding to the respective recognizable content of the physical note to which the digital note corresponds; identifying a background region of the digital note; and setting pixel values from the background region of the particular digital note to a uniform background pixel value. 
     Example 15 
     The method of any combination of examples 1-14, wherein the physical note to which the digital note corresponds includes a first colored region and a second colored region, the method further comprising: identifying, for the digital note, the first colored region and a second colored region; determining an angle formed by an axis of the digital note and a line connecting a feature of the first colored region and a feature of the second colored region; and rotating the digital note based on the determined angle. 
     Example 16 
     A computing device comprising: a memory configured to store digital notes; and one or more processors configured to: receive a digital note of a plurality of digital notes generated based on image data comprising a visual representation of a scene that includes a plurality of physical notes such that each of the plurality of digital notes respectively corresponds to a particular physical note of the plurality of physical notes, wherein each of the physical notes includes respective recognizable content; receive user input indicating a modification to one or more visual characteristics of the digital note; edit, in response to the user input, the one or more visual characteristics of the digital note; and output, for display, a modified version of the digital note that includes the one or more visual characteristics. 
     Example 17 
     The computing device of example 16, wherein the one or more processors are configured to perform the method any combination of examples 1-15. 
     Example 18 
     A computing system comprising: means for receiving a digital note of a plurality of digital notes generated based on image data comprising a visual representation of a scene that includes a plurality of physical notes such that each of the plurality of digital notes respectively corresponds to a particular physical note of the plurality of physical notes, wherein each of the physical notes includes respective recognizable content; means for receiving user input indicating a modification to one or more visual characteristics of the digital note; means for editing, in response to the user input, the one or more visual characteristics of the digital note; and means for outputting, for display, a modified version of the digital note that includes the one or more visual characteristics. 
     Example 19 
     The computing system of example 18, further comprising means for performing the method any combination of examples 1-15. 
     Example 20 
     A computer-readable storage medium storing instructions that, when executed, cause one or more processors of a device to: receive a digital note of a plurality of digital notes generated based on image data comprising a visual representation of a scene that includes a plurality of physical notes such that each of the plurality of digital notes respectively corresponds to a particular physical note of the plurality of physical notes, wherein each of the physical notes includes respective recognizable content; receive user input indicating a modification to one or more visual characteristics of the digital note; edit, in response to the user input, the one or more visual characteristics of the digital note; and output, for display, a modified version of the digital note that includes the one or more visual characteristics. 
     Example 21 
     The computer-readable storage medium of example 20, further storing instructions that cause the one or more processors to perform the method any combination of examples 1-15. 
     Example 22 
     A method comprising: receiving, by a computing device, an input image of an environment having a plurality of physical notes; processing the input image with the computing device to identify the plurality of physical notes in the input image; generating, by the computing device, a plurality of digital notes corresponding to the plurality of notes identified in the input image, wherein the plurality of digital notes include information represented by the plurality of notes in the input image; displaying, on a first portion of a graphical user interface of the computing device, the input image overlaid with the plurality of digital notes in place of the identified plurality of notes; and displaying, by the computing device, a set of one or more of the plurality of digital notes on a second portion of the graphical user interface, wherein each of the digital notes in the set of digital notes displayed in the second portion corresponds to a respective one of the plurality of digital notes displayed in the first portion and overlaid on the input image. 
     Example 23 
     The method of example 21, further comprising: receiving, by the computing device, a user input selecting for deletion at least one of the plurality of digital notes displayed in the first portion of the graphical user interface; and removing, by the computing device and from the set of digital notes displayed in the second portion of the graphical user interface, digital notes that correspond to the digital notes of the first portion of the graphical user interface selected for deletion. 
     Example 24 
     The method of any combination of examples 22-23, wherein the plurality of digital notes from the first portion is greater than the plurality of digital notes in the second portion, the method further comprising: receiving, by the computing device, a user input selecting at least one of the digital notes from the first portion that is not displayed in the second portion; and adding, by the computing device, the selected digital note from the first portion to the set of digital notes displayed on the second portion. 
     Example 25 
     The method of any combination of examples 22-24, further comprising: receiving, by the computing device, a user input selecting a subset of the plurality of digital notes; and grouping, by the computing device, the selected subset of digital notes to form one or more groups. 
     Example 26 
     The method of any combination of examples 22-25, wherein the one or more groups are organized accordingly to a group hierarchy defined by the user input. 
     Example 27 
     A computer system configured to execute the method of any of examples 22-26. 
     Example 28 
     A non-transitory computer-readable medium comprising instructions for causing a programmable processor to execute the method of any of examples 22-26. 
     Example 29 
     A computing device comprising: a processor; an image collection module executable by the processor and configured to receive an input image of an environment having a plurality of physical notes; an image processing engine executable by the processor and configured to identify the plurality of physical notes in the input image and generate a plurality of digital notes corresponding to the plurality of notes identified in the input image, wherein the plurality of digital notes include information represented by the plurality of notes in the input image; and a graphical user interface configured to display the input image overlaid with the plurality of digital notes in place of the identified plurality of notes on a first portion of the graphical user interface and to display a set of one or more of the digital notes on a second portion of the graphical user interface. 
     Example 30 
     The device of example 29, wherein the image collection module includes an image capture device configured to capture the input image. 
     Example 31 
     The device of any combination of examples 29-30, wherein the image collection module includes a communication interface configured to receive the input image. 
     Example 32 
     The device of any combination of examples 29-31, wherein the communication interface includes a wireless communication device configured to receive the input image. 
     Example 33 
     The device of any combination of examples 29-32, wherein the communication interface includes a wired communication device configured to receive the input image. 
     Example 34 
     The device of any combination of examples 29-33, wherein the user interface is further configured to: receive a user input selecting for deletion at least one of the plurality of digital notes displayed in the first portion of the graphical user interface; and remove, from the set of digital notes displayed in the second portion of the graphical user interface, any of the digital notes that correspond to the digital notes of the first portion of the graphical user interface selected for deletion. 
     Example 35 
     The device of any combination of examples 29-34, wherein the plurality of digital notes from the first portion is greater than the plurality of digital notes in the second portion the image processing engine is further configured to: receive a user input selecting at least one of the plurality of digital notes from the first portion that is not in the second portion; and add the selected plurality of digital notes from the first portion to the second portion. 
     Example 36 
     The device of any combination of examples 29-35, wherein the image processing engine is further configured to: receive a user input selecting at least one of the plurality of digital notes between the first portion and the second portion; and group the selected plurality of digital notes between the first portion and the second portion to form one or more groups. 
     Example 37 
     The device of any combination of examples 29-36, wherein the one or more groups are organized accordingly to a group hierarchy defined by the user input. 
     Example 38 
     The device of any combination of examples 29-37, wherein the image processing engine is further configured to display indications of the one or more groups in conjunction with the plurality of digital notes presented on the first portion. 
     Example 39 
     The device of any combination of examples 29-38, wherein the image processing engine is further configured to display indications of the one or more groups in conjunction with the plurality of digital notes presented on the second portion. 
     Example 40 
     A method comprising: receiving, by a computing device, an input image; identifying, by the computing device, a plurality of notes in the input image; editing, by the computing device, background colors from one or more of the plurality of notes identified in the input image; generating, by the computing device, a plurality of digital notes corresponding to the plurality of notes identified in the input image, the plurality of digital notes incorporating the edited background colors; storing, by the computing device, the plurality of digital notes to a digital data storage device for retrieval by a user, wherein the plurality of digital notes include information represented by the plurality of notes in the input image. 
     Example 41 
     The method of example 40, wherein the computing device utilizes a shape detection module to identify at least one of the plurality of notes based on shapes defined by perimeters of the plurality of notes in the input image 
     Example 42 
     The method of any combination of examples 40-41, wherein identifying the plurality of notes in the input image includes identifying the plurality of notes according to color spaces associated with background colors the plurality of notes. 
     Example 43 
     The method of any combination of examples 40-42, wherein the computing device utilizes a pattern detection module to identify at least one of the plurality of notes, wherein the pattern detection module is comprised of pattern recognition algorithms including at least one of a group consisting of: a support vector machine algorithm; a cross-correlation algorithm; and a template matching algorithm. 
     Example 44 
     The method of any combination of examples 40-43, wherein generating the plurality of digital notes further comprises correcting, by the computing device, shadows, lighting, rotation, and scaling of notes in the input image. 
     Example 45 
     The method of any combination of examples 40-44, wherein the input image includes at least one of a group consisting of: a digital image; a digital video; and a continuous digital scan. 
     Example 46 
     The method of any combination of examples 40-45, wherein the plurality of notes in the input image includes at least one of a group consisting of: a 7.62×7.62 centimeter (cm) note; a 66.04×99.06 cm poster; a triangular metal sign; a sticker; and a 8.5×11 in sheet of paper. 
     Example 47 
     The method of any combination of examples 39-45, wherein generating the plurality of digital notes includes, for each of the plurality of digital notes, incorporating, in the digital note, visual information of the corresponding note in the input image. 
     Example 48 
     A computer system configured to execute the method of any combination of examples 40-47. 
     Example 49 
     A non-transitory computer-readable medium comprising instructions for causing a programmable processor to execute the method of any combination of examples 40-47. 
     Example 50 
     A computing device comprising: an image collection module configured to receive an input image; an image processing engine configured to identify a plurality of notes in the input image received by the image collection module, and generate a plurality of digital notes corresponding to the plurality of notes identified in the input image, wherein the plurality of digital notes include information represented by the plurality of notes in the input image; and a digital data storage device configured to store the plurality of digital notes generated by the image processing module for retrieval by a user. 
     Example 51 
     The device of example 50, wherein the image collection module includes an image capture device configured to capture the input image. 
     Example 52 
     The device of any combination of examples 50-51, wherein the image collection module includes a communication interface configured to receive the input image. 
     Example 53 
     The device of any combination of examples 50-52, wherein the communication interface includes a wireless communication device configured to receive the input image. 
     Example 54 
     The device of any combination of examples 50-53, wherein the communication interface includes a wired communication device configured to receive the input image. 
     Example 55 
     The device of any combination of examples 50-54, wherein the digital data storage device is configured to store the input image. 
     Example 56 
     The device of any combination of examples 50-55, wherein the image processing engine includes a shape detection module configured to identify at least one of the plurality of notes based on shapes defined by perimeters of the plurality of notes in the input image. 
     Example 57 
     The device of any combination of examples 50-56, wherein the image processing engine is further configured to identify the plurality of notes in the input image includes identifying the plurality of notes according to color spaces associated with background colors the plurality of notes. 
     Example 58 
     The device of any combination of examples 50-57, wherein the image processing engine includes a pattern detection module configured to identify at least one of the plurality of notes, wherein the pattern detection module is comprised of pattern recognition algorithms including at least one of a group consisting of: a support vector machine algorithm; a cross-correlation algorithm; and a template matching algorithm. 
     Example 59 
     The device of any combination of examples 50-58, wherein the image processing engine is further configured to correct shadows, lighting, rotation, and scaling of notes in the input image. 
     Example 60 
     The device of any combination of examples 50-59, wherein the input image includes at least one of a group consisting of: a digital image; a digital video; and a continuous digital scan. 
     Example 61 
     The device of any combination of examples 50-60, wherein the plurality of notes in the input image includes at least one of a group consisting of: a 7.62×7.62 centimeter (cm) note; a 66.04×99.06 cm poster; a triangular metal sign; a sticker; and a 8.5×11 in sheet of paper. 
     Example 62 
     The device of any combination of examples 50-61, wherein the image processing engine is further configured to, for each of the plurality of digital notes, incorporate, in the digital note, visual information of the corresponding note in the input image. 
     The techniques described in this disclosure may be implemented, at least in part, in hardware, software, firmware, or any combination thereof. For example, various aspects of the described techniques, including the disclosed mobile device  15 ,  16 , cloud  12 , and/or computer system  14 , may be implemented within one or more processors, including one or more microprocessors, digital signal processors (DSPs), application specific integrated circuits (ASICs), field programmable gate arrays (FPGAs), or any other equivalent integrated or discrete logic circuitry, as well as any combinations of such components. 
     Such hardware, software, and firmware may be implemented within the same device or within separate devices to support the various techniques described in this disclosure. In addition, any of the described units, modules, or components may be implemented together or separately as discrete but interoperable logic devices. Depiction of different features as modules or units is intended to highlight different functional aspects and does not necessarily imply that such modules or units must be realized by separate hardware, firmware, or software components. Rather, functionality associated with one or more modules or units may be performed by separate hardware, firmware, or software components, or integrated within common or separate hardware, firmware, or software components. 
     The techniques described in this disclosure may also be embodied or encoded in a computer-readable medium, such as a transitory or non-transitory computer-readable storage medium, containing instructions. Instructions embedded or encoded in a computer-readable medium, including a computer-readable storage medium, may cause one or more programmable processors, or other processors, such one or more processors included in a control system, to implement one or more of the techniques described herein, such as when instructions included or encoded in the computer-readable medium are executed by the one or more processors. Non-transitory computer-readable storage media may include random access memory (RAM), read only memory (ROM), programmable read only memory (PROM), erasable programmable read only memory (EPROM), electronically erasable programmable read only memory (EEPROM), flash memory, a hard disk, a compact disc ROM (CD-ROM), a floppy disk, a cassette, magnetic media, optical media, or other computer-readable media. In some examples, an article of manufacture may comprise one or more computer-readable storage media. 
     Various examples of this disclosure have been described. These and other examples are within the scope of the following claims.