Patent Publication Number: US-2009220120-A1

Title: System and method for artistic scene image detection

Description:
BACKGROUND OF THE INVENTION 
     The subject application is directed generally to analysis or classification of encoded images and is particularly suited for detection of artistic scenes in electronic images. 
     Electronic images are created or captured in many ways, such as from digital still cameras, digital motion cameras, digital imaging software, or the like. Skilled photographers create artistic images that have properties specifically chosen for effect. Such effects may include unusual color balances, dominance of one or more hues, or use of limited color spectra. Earlier photographers obtained such effects by strategic placement of lighting, such as with a sunset, use of color filters on lenses, or by a particular environment such as with an underwater shooting. Such effects may also be accomplished with close-ups, sepia, higher speed or lower speed image capturing, diffusion filters, or mood lighting. 
     With digital images, computational enhancements are frequently made, such as white balancing, color adjustment, and the like. Application of such enhancements is not desirable when artistic images are deliberately created. 
     SUMMARY OF THE INVENTION 
     In accordance with one embodiment of the subject application, there is provided a system and method for analysis or classification of encoded images. 
     Further in accordance with one embodiment of the subject application, there is provided a system and method for detection of artistic scenes in electronic images. 
     Still further in accordance with one embodiment of the subject application, there is provided a system for artistic scene image detection. The system comprises means adapted for receiving image data encoded in a multi-dimensional color space and means adapted for calculating histogram data from received image data. The system also comprises means adapted for identifying dominant spike regions in calculated histogram data and testing means for testing a calculated N-sum value against a predetermined threshold value. The system further comprises classifying means adapted for classifying received image data as at least one of an artistic scene, a tinted artistic scene, and a sepia tone range artistic scene in accordance with an output of the testing means. 
     In one embodiment of the subject application, the system further includes means adapted for identifying near achromatic pixels in received image data and means adapted for selectively discarding identified near achromatic pixels prior to calculation of histogram data therefrom. 
     In another embodiment of the subject application, the system also includes means adapted for receiving input image data and means adapted for converting received input image data into the image data encoded in HSV color space. 
     In a further embodiment of the subject application, the system also comprises means adapted for down-sizing image data prior to calculation of histogram data therefrom. 
     Still further, in accordance with one embodiment of the subject application, there is provided a method for artistic scene image detection in accordance with the system as set forth above. 
     Still other advantages, aspects, and features of the subject application will become readily apparent to those skilled in the art from the following description, wherein there is shown and described a preferred embodiment of the subject application, simply by way of illustration of one of the modes best suited to carry out the subject application. As it will be realized, the subject application is capable of other different embodiments, and its several details are capable of modifications in various obvious aspects, all without departing from the scope of the subject application. Accordingly, the drawings and descriptions will be regarded as illustrative in nature and not as restrictive. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
       The patent or application file contains at least one drawing executed in color. Copies of this patent or patent application publication with color drawing(s) will be provided by the Office upon request and payment of the necessary fee. 
       The subject application is described with reference to certain figures, including: 
         FIG. 1  is an overall diagram of a system for artistic scene image detection according to one embodiment of the subject application; 
         FIG. 2  is a block diagram illustrating controller hardware for use in the system for artistic scene image detection according to one embodiment of the subject application; 
         FIG. 3  is a functional diagram illustrating the controller for use in the system for artistic scene image detection according to one embodiment of the subject application; 
         FIG. 4A  is an example image for use with the system and method for artistic scene image detection according to one embodiment of the subject application; 
         FIG. 4B  is an example image illustrating the artistic manipulation of the image of  FIG. 4A  for use with the system and method for artistic scene image detection according to one embodiment of the subject application; 
         FIG. 4C  is an example image illustrating erroneous automatic image correction of the image of  FIG. 4B  for use with the system and method for artistic scene image detection according to one embodiment of the subject application; 
         FIG. 5A  is an example artistic scene image for use with the system and method for artistic scene image detection according to one embodiment of the subject application; 
         FIG. 5B  is a normalized histogram in hue corresponding to the image of  FIG. 5A  for use with the system and method for artistic scene image detection according to one embodiment of the subject application; 
         FIG. 6A  illustrates a hue ramp for use in the system and method for artistic scene image detection according to one embodiment of the subject application; 
         FIG. 6B  illustrates a partitioned hue ramp for use in the system and method for artistic scene image detection according to one embodiment of the subject application; 
         FIG. 7A  is another example image for use with the system and method for artistic scene image detection according to one embodiment of the subject application; 
         FIG. 7B  is a hue histogram in HSV corresponding to the image of  FIG. 7A  for use with the system and method for artistic scene image detection according to one embodiment of the subject application; 
         FIG. 7C  is a de-noised hue histogram corresponding to the input image of  FIG. 7A  for use with the system and method for artistic scene image detection according to one embodiment of the subject application; 
         FIG. 7D  is an illustration of the input image of  FIG. 7A  depicting the discarded pixels in accordance with the de-noising histogram of  FIG. 7C  for use with the system and method for artistic scene image detection according to one embodiment of the subject application; 
         FIG. 8A  is an example artistic scene image for use in the system and method for artistic scene image detection according to one embodiment of the subject application; 
         FIG. 8B  is a normalized histogram in hue corresponding to the image of  FIG. 8A  for use with the system and method for artistic scene image detection according to one embodiment of the subject application; 
         FIG. 9A  is another example artistic scene image for use with the system and method for artistic scene image detection according to one embodiment of the subject application; 
         FIG. 9B  is a normalized histogram in hue corresponding to the image of  FIG. 9A  for use with the system and method for artistic scene image detection according to one embodiment of the subject application; 
         FIG. 10A  illustrates several artistic scene images for use with the system and method for artistic scene image detection according to one embodiment of the subject application; 
         FIG. 10B  illustrates the images of  FIG. 10A  after erroneous automatic correction for use with the system and method for artistic scene image detection according to one embodiment of the subject application; 
         FIG. 11A  illustrates plots of hue angles at a first spike for a plurality of input images in accordance with the system and method for artistic scene image detection according to one embodiment of the subject application; 
         FIG. 11B  illustrates plots of hue angles at a second spike for a plurality of input images in accordance with the system and method for artistic scene image detection according to one embodiment of the subject application; 
         FIG. 11C  illustrates plots of hue angles at a third spike for a plurality of input images in accordance with the system and method for artistic scene image detection according to one embodiment of the subject application; 
         FIG. 12A  illustrates plots of combined 3-sums at first and second spikes in accordance with the system and method for artistic scene image detection according to one embodiment of the subject application; 
         FIG. 12B  illustrates plots of combined 5-sums at first and second spikes in accordance with the system and method for artistic scene image detection according to one embodiment of the subject application; 
         FIG. 12C  illustrates plots of combined 7-sums at first and second spikes in accordance with the system and method for artistic scene image detection according to one embodiment of the subject application; 
         FIG. 13  is an illustration of the relationship of various artistic image types in accordance with the system and method for artistic scene image detection according to one embodiment of the subject application; 
         FIG. 14  is a flowchart illustrating a method for artistic scene image detection according to one embodiment of the subject application; and 
         FIG. 15  is a flowchart illustrating a method for artistic scene image detection according to one embodiment of the subject application. 
     
    
    
     DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENT 
     The subject application is directed to a system and method for analysis or classification of encoded images. In particular, the subject application is directed to a system and method for detection of artistic scenes in electronic images. It will become apparent to those skilled in the art that the system and method described herein are suitably adapted to a plurality of varying electronic fields employing electronic analysis including, for example and without limitation, communications, general computing, data processing, document processing, or the like. The preferred embodiment, as depicted in  FIG. 1 , illustrates a document processing field for example purposes only and is not a limitation of the subject application solely to such a field. The skilled artisan will appreciate that, as used herein, an artistic image or scene corresponds to an image created deliberately by a person knowledgeable in photography, e.g., image effects that would otherwise be problematic or unintentional, or would otherwise detract from the underlying image. Such examples, as will be understood by those skilled in the art, include, without limitation, unusual color balance, predominance of one or a small number of hues, lighter or darker than typical, unusual contrast, and the like. 
     Referring now to  FIG. 1 , there is shown an overall diagram of a system  100  for artistic scene image detection in accordance with one embodiment of the subject application. As shown in  FIG. 1 , the system  100  is capable of implementation using a distributed computing environment, illustrated as a computer network  102 . It will be appreciated by those skilled in the art that the computer network  102  is any distributed communications system known in the art that is capable of enabling the exchange of data between two or more electronic devices. The skilled artisan will further appreciate that the computer network  102  includes, for example and without limitation, a virtual local area network, a wide area network, a personal area network, a local area network, the Internet, an intranet, or any suitable combination thereof. In accordance with the preferred embodiment of the subject application, the computer network  102  is comprised of physical layers and transport layers, as illustrated by the myriad conventional data transport mechanisms such as, for example and without limitation, Token-Ring, 802.11(x), Ethernet, or other wireless or wire-based data communication mechanisms. The skilled artisan will appreciate that, while a computer network  102  is shown in  FIG. 1 , the subject application is equally capable of use in a stand-alone system, as will be known in the art. 
     The system  100  also includes a document processing device  104 , depicted in  FIG. 1  as a multifunction peripheral device suitably adapted to perform a variety of document processing operations. It will be appreciated by those skilled in the art that such document processing operations include, for example and without limitation, facsimile, scanning, copying, printing, electronic mail, document management, document storage, or the like. Suitable commercially available document processing devices include, for example and without limitation, the Toshiba e-Studio Series Controller. In accordance with one aspect of the subject application, the document processing device  104  is suitably adapted to provide remote document processing services to external or network devices. Preferably, the document processing device  104  includes hardware, software, and any suitable combination thereof configured to interact with an associated user, a networked device, or the like. 
     According to one embodiment of the subject application, the document processing device  104  is suitably equipped to receive a plurality of portable storage media including, without limitation, Firewire drive, USB drive, SD, MMC, XD, Compact Flash, Memory Stick, and the like. In the preferred embodiment of the subject application, the document processing device  104  further includes an associated user interface  106 , such as a touch-screen, LCD display, touch-panel, alpha-numeric keypad, or the like, via which an associated user is able to interact directly with the document processing device  104 . In accordance with the preferred embodiment of the subject application, the user interface  106  is advantageously used to communicate information to the associated user and receive selections from the associated user. The skilled artisan will appreciate that the user interface  106  comprises various components suitably adapted to present data to the associated user, as are known in the art. In accordance with one embodiment of the subject application, the user interface  106  comprises a display suitably adapted to display one or more graphical elements, text data, images, or the like to an associated user; receive input from the associated user; and communicate the same to a backend component such as a controller  108 , as is explained in greater detail below. Preferably, the document processing device  104  is communicatively coupled to the computer network  102  via a suitable communications link  112 . As will be understood by those skilled in the art, suitable communications links include, for example and without limitation, WiMax, 802.11a, 802.11b, 802.11g, 802.11(x), Bluetooth, the public switched telephone network, a proprietary communications network, infrared, optical, or any other suitable wired or wireless data transmission communications known in the art. 
     In accordance with one embodiment of the subject application, the document processing device  104  further incorporates a backend component, designated as the controller  108 , suitably adapted to facilitate the operations of the document processing device  104 , as will be understood by those skilled in the art. Preferably, the controller  108  is embodied as hardware, software, or any suitable combination thereof configured to control the operations of the associated document processing device  104 , facilitate the display of images via the user interface  106 , direct the manipulation of electronic image data, and the like. For purposes of explanation, the controller  108  is used to refer to any of the myriad components associated with the document processing device  104 , including hardware, software, or combinations thereof functioning to perform, cause to be performed, control, or otherwise direct the methodologies described hereinafter. It will be understood by those skilled in the art that the methodologies described with respect to the controller  108  are capable of being performed by any general purpose computing system known in the art, and thus the controller  108  is representative of such a general computing device and is intended as such when used hereinafter. Furthermore, the use of the controller  108  hereinafter is for the example embodiment only, and other embodiments, which will be apparent to one skilled in the art, are capable of employing the system and method for artistic scene image detection of the subject application. The functioning of the controller  108  will better be understood in conjunction with the block diagrams illustrated in  FIGS. 2 and 3 , explained in greater detail below. 
     Communicatively coupled to the document processing device  104  is a data storage device  110 . In accordance with the preferred embodiment of the subject application, the data storage device  110  is any mass storage device known in the art including, for example and without limitation, magnetic storage drives, a hard disk drive, optical storage devices, flash memory devices, or any suitable combination thereof. In the preferred embodiment, the data storage device  110  is suitably adapted to store document data, image data, electronic database data, or the like. It will be appreciated by those skilled in the art that, while illustrated in  FIG. 1  as being a separate component of the system  100 , the data storage device  110  is capable of being implemented as an internal storage component of the document processing device  104 , a component of the controller  108 , or the like such as, for example and without limitation, an internal hard disk drive or the like. 
     The system  100  illustrated in  FIG. 1  further depicts a user device  114  in data communication with the computer network  102  via a communications link  116 . It will be appreciated by those skilled in the art that the user device  114  is shown in  FIG. 1  as a laptop computer for illustration purposes only. As will be understood by those skilled in the art, the user device  114  is representative of any personal computing device known in the art including, for example and without limitation, a computer workstation, a personal computer, a personal data assistant, a web-enabled cellular telephone, a smart phone, a proprietary network device, or other web-enabled electronic device. The communications link  116  is any suitable channel of data communications known in the art including but not limited to wireless communications, for example and without limitation, Bluetooth, WiMax, 802.11a, 802.11b, 802.11g, 802.11(x), a proprietary communications network, infrared, optical, the public switched telephone network, or any suitable wireless data transmission system or wired communications known in the art. Preferably, the user device  114  is suitably adapted to generate and transmit electronic images, document processing instructions, user interface modifications, upgrades, updates, personalization data, or the like to the document processing device  104  or any other similar device coupled to the computer network  102 . In accordance with one embodiment of the subject application, the user device  114  is suitably adapted to perform image processing operations in accordance with the subject application. 
     Turning now to  FIG. 2 , illustrated is a representative architecture of a suitable backend component, i.e., the controller  200 , shown in  FIG. 1  as the controller  108 , on which operations of the subject system  100  are completed. The skilled artisan will understand that the controller  108  is representative of any general computing device known in the art that is capable of facilitating the methodologies described herein. Included is a processor  202  suitably comprised of a central processor unit. However, it will be appreciated that the processor  202  may be advantageously composed of multiple processors working in concert with one another, as will be appreciated by one of ordinary skill in the art. Also included is a non-volatile or read only memory  204 , which is advantageously used for static or fixed data or instructions, such as BIOS functions, system functions, system configuration data, and other routines or data used for operation of the controller  200 . 
     Also included in the controller  200  is random access memory  206  suitably formed of dynamic random access memory, static random access memory, or any other suitable, addressable, and writable memory system. Random access memory  206  provides a storage area for data instructions associated with applications and data handling accomplished by the processor  202 . 
     A storage interface  208  suitably provides a mechanism for non-volatile, bulk, or long term storage of data associated with the controller  200 . The storage interface  208  suitably uses bulk storage, such as any suitable addressable or serial storage such as a disk, optical, tape drive, and the like, as shown as  216 , as well as any suitable storage medium, as will be appreciated by one of ordinary skill in the art. 
     A network interface subsystem  210  suitably routes input and output from an associated network, allowing the controller  200  to communicate to other devices. The network interface subsystem  210  suitably interfaces with one or more connections with external devices to the controller  200 . By way of example, illustrated is at least one network interface card  214  for data communication with fixed or wired networks such as Ethernet, token ring, and the like and a wireless interface  218  suitably adapted for wireless communication via means such as WiFi, WiMax, wireless modem, cellular network, or any suitable wireless communication system. It is to be appreciated however, that the network interface subsystem  210  suitably utilizes any physical or non-physical data transfer layer or protocol layer, as will be appreciated by one of ordinary skill in the art. In the illustration, the network interface card  214  is interconnected for data interchange via a physical network  220  suitably comprised of a local area network, wide area network, or a combination thereof. 
     Data communication between the processor  202 , read only memory  204 , random access memory  206 , storage interface  208 , and the network interface subsystem  210  is suitably accomplished via a bus data transfer mechanism, such as illustrated by bus  212 . 
     Also in data communication with the bus  212  is a document processor interface  222 . The document processor interface  222  suitably provides connection with hardware  232  to perform one or more document processing operations. Such operations include copying accomplished via copy hardware  224 , scanning accomplished via scan hardware  226 , printing accomplished via print hardware  228 , and facsimile communication accomplished via facsimile hardware  230 . It is to be appreciated that the controller  200  suitably operates any or all of the aforementioned document processing operations. Systems accomplishing more than one document processing operation are commonly referred to as multifunction peripherals or multifunction devices. 
     Functionality of the subject system  100  is accomplished on a suitable document processing device, such as the document processing device  104 , which includes the controller  200  of  FIG. 2  (shown in  FIG. 1  as the controller  108 ) as an intelligent subsystem associated with a document processing device. In the illustration of  FIG. 3 , controller function  300  in the preferred embodiment includes a document processing engine  302 . A suitable controller functionality is that incorporated into the Toshiba e-Studio system in the preferred embodiment.  FIG. 3  illustrates suitable functionality of the hardware of  FIG. 2  in connection with software and operating system functionality, as will be appreciated by one of ordinary skill in the art. 
     In the preferred embodiment, the engine  302  allows for printing operations, copy operations, facsimile operations and scanning operations. This functionality is frequently associated with multi-function peripherals, which have become a document processing peripheral of choice in the industry. It will be appreciated, however, that the subject controller does not have to have all such capabilities. Controllers are also advantageously employed in dedicated or more limited-purpose document processing devices that can perform one or more of the document processing operations listed above. 
     The engine  302  is suitably interfaced to a user interface panel  310 , which panel  310  allows for a user or administrator to access functionality controlled by the engine  302 . Access is suitably enabled via an interface local to the controller or remotely via a remote thin or thick client. 
     The engine  302  is in data communication with print function  304 , facsimile function  306 , and scan function  308 . These functions facilitate the actual operation of printing, facsimile transmission and reception, and document scanning for use in securing document images for copying or generating electronic versions. 
     A job queue  312  is suitably in data communication with the print function  304 , facsimile function  306 , and scan function  308 . It will be appreciated that various image forms, such as bit map, page description language or vector format, and the like, are suitably relayed from the scan function  308  for subsequent handling via the job queue  312 . 
     The job queue  312  is also in data communication with network services  314 . In a preferred embodiment, job control, status data, or electronic document data is exchanged between the job queue  312  and the network services  314 . Thus, a suitable interface is provided for network-based access to the controller function  300  via client side network services  320 , which is any suitable thin or thick client. In the preferred embodiment, the web services access is suitably accomplished via a hypertext transfer protocol, file transfer protocol, uniform data diagram protocol, or any other suitable exchange mechanism. The network services  314  also advantageously supplies data interchange with client side services  320  for communication via FTP, electronic mail, TELNET, or the like. Thus, the controller function  300  facilitates output or receipt of electronic document and user information via various network access mechanisms. 
     The job queue  312  is also advantageously placed in data communication with an image processor  316 . The image processor  316  is suitably a raster image process, page description language interpreter, or any suitable mechanism for interchange of an electronic document to a format better suited for interchange with device functions such as print  304 , facsimile  306 , or scan  308 . 
     Finally, the job queue  312  is in data communication with a job parser  318 , which job parser  318  suitably functions to receive print job language files from an external device, such as client device services  322 . The client device services  322  suitably include printing, facsimile transmission, or other suitable input of an electronic document for which handling by the controller function  300  is advantageous. The job parser  318  functions to interpret a received electronic document file and relay it to the job queue  312  for handling in connection with the afore-described functionality and components. 
     In operation, image data encoded in a multi-dimensional color space is first received. Histogram data is then calculated from the received image data. Dominant spike regions in the calculated histogram data are then identified, and an N-sum value of the identified spike regions is calculated. A calculated N-sum value is then tested against a predetermined threshold value. Received image data is then classified as an artistic scene, a tinted artistic scene, or a sepia tone range artistic scene, in accordance with an output of the testing of the calculated N-sum value against the predetermined threshold value. 
     In accordance with one embodiment of the subject application, input image data is received by the controller  108  or other suitable component associated with the document processing device  104 , the user device  114 , or the like. As will be understood by those skilled in the art, any suitable device capable of performing image processing operations is capable of being used in accordance with the implementation of the subject application described herein. The skilled artisan will further appreciate that the receipt of input image data corresponds to image data communicated via the computer network  102 , generated via operations of the document processing device  104 , retrieved from a suitable storage device, or the like. It will also be appreciated by those skilled in the art that the image data is capable of being received in a variety of image formats, e.g., JPEG, TIFF, RAW, PDF, BMP, GIF, or the like. According to one embodiment of the subject application, the image data is suitably encoded in a multi-dimensional color space such as, for example and without limitation, RGB, CMYK, CIE L*a*b*, YC b C r , YIQ, HSV, xyY, u′v′Y, L*u*v*, or the like. 
       FIG. 4A  illustrates an example input image  402  corresponding to a normal street scene, as will be appreciated by those skilled in the art. It will be understood by those skilled in the art that, during typical operations of an associated document processing device  104  equipped for automatic image enhancement, image attributes are capable of being mistakenly adjusted. FIG.  4 B illustrates an artistically tinted image  404  corresponding to the input image  402  of  FIG. 4A . The skilled artisan will appreciate that the artistically tinted image  404  represents the input image  402  after the image  402  was tinted by a suitable photographic or image editing application, e.g., PICASA or the like.  FIG. 4C  illustrates an erroneous, or mistaken, application of automatic image correction via the image  406 . Thus, the image  406  illustrates the result of an attempt at automatic color correction, resulting in the removal of the intentionally applied artistic scene. 
     The controller  108  or other suitable component associated with the document processing device  104 , the user device  114 , or the like then down-sizes the received image data upon a determination that the image data as received would require substantial resources on the part of the processing device, e.g., the controller  108 , the user device  114 , etc. That is, the received input image data represents a substantially large image file, which would use a high percentage of available processing resources. The skilled artisan will appreciate that such down-sizing of image data corresponds, for example and without limitation, to the “blurring” and/or “down-sampling” of the received input image data or other reduction in the total number of pixels in an image, as will be known in the art. In addition, when the received input image data is not in a desirable format, i.e., the image data is not in HSV (hue, saturation, value (brightness)) color space, the controller  108  or other component associated with the document processing device  104 , the user device  114 , or the like then converts the received image data into HSV encoded image data. 
     Near achromatic pixels in the received input image data are then identified in accordance with the system and method described in co-pending patent application Ser. No. 12/037,711, the entirety of which is incorporated herein by reference. Those skilled in the art will appreciate that near achromatic pixels correspond to those pixels in an image having no color (achromatic) or those pixels that are almost achromatic. The near achromatic pixels identified by the controller  108  or other suitable component associated with the document processing device  104 , the user device  114 , or the like are then selectively discarded in accordance with the subject application. Histogram data is then calculated from the received image data following the discarding of the selected near achromatic pixels. In accordance with one embodiment of the subject application, the histogram data corresponds to a normalized histogram in hue with the selected near achromatic pixels discarded. 
     The skilled artisan will appreciate that, typically, one class of artistic scenes has a characteristic of color (hue) concentrations, i.e., the scene includes the presence of one or two dominant colors. Such presence is capable of being detected, as discussed in greater detail below, via a normalized hue histogram that is generated from a received input image.  FIGS. 5A and 5B  illustrate such a received input image  502  and associated normalized hue histogram  504 . Thus, the hue histogram generated from the received artistic scene image  502  depicted in  FIG. 5A  generally has one or two “spikes” or “peaks,” as represented in the hue histogram  504  of  FIG. 5B . The skilled artisan will appreciate that the hue ramp  506  associated with the hue histogram  504  of  FIG. 5B  indicates that there is a hue concentration, or spike, at the green color, e.g., approximately 45% of the total pixels in the image  502  are green. The skilled artisan will appreciate that additional examples of such histograms are discussed with respect to  FIGS. 6A-13 , referenced in greater detail below. 
     From the calculated histogram data, the dominant spike regions are then identified. An N-sum value of the identified spikes of the histogram data is then calculated. Use and calculation of the N-sum value is explained in greater detail with respect to  FIGS. 4A-13 , discussed below. The N-sum value is then tested against a predetermined threshold value to determine whether the calculated N-sum value is within a predetermined range of the threshold value. When the N-sum value does fall within the predetermined range of the threshold value, the received input image is classified as an artistic scene image, whereupon no automatic image correction is undertaken on the image by the associated controller  108  or other suitable component of the document processing device  104 , the user device  114 , or the like. In the event that the calculated N-sum value falls outside the predetermined range of the threshold value, the received image is classified as a non-artistic scene, and any suitable automatic image correction is capable of being performed by the associated component of the document processing device  104 , the user device  114 , or the like. 
     The foregoing will be better understood in conjunction with the example illustrations of  FIGS. 6A-13 , which explain but do not limit the subject system and method for artistic scene detection in accordance with the subject application. Turning now to  FIGS. 6A-13 , there are shown several example implementations of the subject application for artistic scene image detection. Thus, in applying the methodology discussed above, a received input image, encoded in a multi-dimensional color space, is first blurred so as to reduce aliasing and then down-sampled, if necessary, so as to increase the speed at which the image is processed via the corresponding reduction in computational costs to the document processing device  104 , the user device  114 , or other device implemented in accordance with the subject application. 
     The input image is then, after blurring and/or down-sampling, converted to HSV (hue, saturation, value (brightness)) color space. It will be understood by those skilled in the art that the input image is capable of being received in HSV color space; however, typically input image data is received in RGB or CMYK color space, thus requiring conversion to HSV color space. The histogram of the image is then calculated in hue and normalized by the total number of pixels associated with the received input image. The skilled artisan will appreciate that the hue angle in HSV is capable of being complicated when the hue angles wrap around or the hue angles are considered as noise when the pixels are achromatic or almost achromatic.  FIG. 6A  illustrates a hue ramp  602  wherein the hue angles wrap around.  FIG. 6B  depicts a hue ramp  604  marked with indices in 100 even partitions, as will be appreciated by those skilled in the art. The wrap-around of hue angles is illustrated in the hue ramp  604  of  FIG. 6B  such that H[i]=i=th histogram count in 100 even partitions between 0.0 and 1.0. For example, if H[1]=count at 0.0 and H[101]=count at 1.0, then H[0]=H[101], H[−1]=H[100], and H[−2]=H[99], and H[102]=H[1], H[103]=H[2] and H[104]=H[3], etc. 
     The near achromatic pixels of the input image are then identified and selectively removed.  FIG. 7A  illustrates an input image  702 ;  FIG. 7B  illustrates a hue histogram  704  in HSV color space corresponding to the input image  702  in which the peaks are noise;  FIG. 7C  illustrates a hue histogram  706  in HSV color space after near achromatic pixels have been discarded, thereby illustrating the real peaks of the input image  702 ; and  FIG. 7D  thus illustrates the discarded pixels, shown as blue in image  708 , as a result of the de-noising performed in accordance with one embodiment of the subject application. Stated another way,  FIGS. 7A-7D  illustrate the de-noising of an input image in accordance with one embodiment of the subject application. Therefore, given an input image, the histogram in H (hue) value is calculated and normalized by the total number of pixels with all near achromatic pixels discarded. For example, a normalized histogram in hue, H[i], equals the percentage of pixels of hue value equal to i in i*360 degrees. 
     The dominant spike or peak regions of the normalized histogram in hue, with near achromatic pixels discarded, are then identified.  FIG. 8A  illustrates an artistic scene input image  802  and  FIG. 8B  illustrates a normalized histogram  804  in hue corresponding thereto. As shown, the histogram  804  includes a single spike or peak region ((e.g., H[i] at I max =35), such that the maximum histogram count is expressed as H max =H[I max ]=0.4979, i.e., after discarding near achromatic pixels, 49.79% of all the pixels remaining are with hue angle 0.36*360=129.60 degrees (shown in the hue ramp  806  as indicating the peak is green). N-sum at i is then defined to be the sum of N closest neighbors centered at i. For example, where N=3, the 3-sum at I max =35 in  FIGS. 8A and 8B  equals the sum of H[34]=0.2838, H[35]=0.4979 and H[36]=0.1466, or 0.9283. For example and without limitation, locating or identifying of the single spike is accomplished by locating the maximum histogram count in hue, H max , at I max , and calculating the N-Sum at I max , if N-Sum&gt;T for some threshold T, then the input image is classified as an artistic scene, where N can be 3, 5, or 7, etc. 
     The skilled artisan will appreciate that some input images are capable of including more than a single spike or peak region.  FIG. 9A  illustrates an artistic input image  902  corresponding to a sepia tone image, and  FIG. 9B  illustrates a corresponding normalized histogram  904  in hue after near achromatic pixels are discarded. The normalized histogram  904  includes two spike or peak regions, which are illustrated in  FIG. 9B .  FIG. 10A  depicts three images  1002 ,  1004 , and  1006  corresponding to sepia tone input images, and  FIG. 10B  depicts three images  1008 ,  1010 , and  1012  corresponding, respectively, to images  1002 ,  1004 , and  1006 , after application of an automatic color correction mechanism, such as that offered in PHOTOSHOP by Adobe Systems, Inc. The skilled artisan will appreciate that, while not shown, each of these images  1002 ,  1004 , and  1006  have histograms with one or more spikes or peak regions. 
     In accordance with one embodiment of the subject application, the identification of more than one spike or peak region is accomplished via locating of all significant spikes in the image, e.g., the associated normalized histogram in hue of the image. For example, searching for all i values such that H[i−1]&lt;H[i]&gt;H[i+1] and H[i]&gt;Th where Th is a pre-determined threshold value, then locating the tallest and the second tallest spikes, H max =H(I max ) and H max2 =H(I max2 ), and then calculating the combined N-Sum, i.e., the sum of the N-Sum&#39;s at I max  and I max2 . Thus, if the combined N-Sum&gt;Th′ for some threshold Th′, then the input image is classified as an artistic scene, where N is capable of equating to 3, 5, 7, or the like. It will be appreciated by those skilled in the art that, when searching for the tallest and second tallest spikes, the fact that the array H[i] wraps around must be taken into account. Furthermore, the skilled artisan will understand that attention is required to remove redundancy in the calculation of the combined N-Sum when the N-Sums of the tallest and second tallest spikes overlap, such as is illustrated in the histogram  904  of  FIG. 9B . 
       FIGS. 11A ,  11 B, and  11 C illustrate plots  1102 ,  1104 , and  1106  of hue angles at a first spike, a second spike, and a third spike, respectively, in accordance with a plurality of observed sepia tone images, e.g., 300 (not shown). The skilled artisan will appreciate that the plot  1102  of  FIG. 11A  corresponds to hue angles associated with the first spike, the plot  1104  of  FIG. 11B  corresponds to the hue angles associated with the second spike, and the plot  1106  of  FIG. 11C  corresponds to the hue angles associated with the third spike. In  FIG. 11A , it is shown that the hue angles of the first spike are clustered within the range of 1 and 18, while some of the observed images do not have second spikes ( FIG. 11B ) and even fewer observed images have third spikes ( FIG. 11C ).  FIG. 12A  illustrates plots  1202  of the combined 3-Sum at the first and second spikes,  FIG. 12B  illustrates plots  1204  of the combined 5-Sum at the first and second spikes, and  FIG. 12C  illustrates plots  1206  of the combined 7-Sum at the first and second spikes. The skilled artisan will thereby appreciate that, for the majority of the observed images, the combined 7-Sum is above 0.9. 
       FIG. 13  shows several types of artistic scenes  1302  and the various relationships between the types. As depicted in  FIG. 13 , the set of artistic scenes  1302  includes the set of artistic images  1304  and the set of sepia images  1308 . The artistic images  1304 , as illustrated in  FIG. 13 , is a superset of tinted images  1306 , and the intersection of tinted images  1306  and sepia images  1308  is represented as the set of simulated sepia images  1310 , e.g., sepia images generated by suitable photographic or image processing applications, e.g., PICASA. The skilled artisan will appreciate that, for the foregoing images and applications of the subject application, the threshold values referenced therein are capable of adjustment in accordance with the applications to which they are applied. For purposes of the analysis above, the threshold values have been optimized for automatic white balance and white stretch (image correction), with T=0.0005, Th=0.998, Th′=0.9 and Th″=0.5 (used in the description of  FIG. 15 , discussed in greater detail below). 
     The skilled artisan will appreciate that the subject system  100  and components described above with respect to  FIGS. 1-13  will be better understood in conjunction with the methodologies described hereinafter with respect to  FIG. 14  and  FIG. 15 . Turning now to  FIG. 14 , there is shown a flowchart  1400  illustrating a method for artistic scene image detection in accordance with one embodiment of the subject application. Beginning at step  1402 , image data, encoded in a multi-dimensional color space, is received. It will be appreciated by those skilled in the art that the multi-dimensional color space is representative of any of the myriad various color spaces associated with image processing in accordance with the subject application including, for example and without limitation, CIE L*a*b*, YC b C r , YIQ, xyY, u′v′Y, L*u*v*, RGB, CMYK, HSV, or the like. Those skilled in the art with also appreciate that the received image data is capable of being received in a variety of image formats, e.g., JPEG, TIFF, RAW, PDF, BMP, GIF, or the like. 
     At step  1404 , histogram data is calculated from the received image data. In accordance with one embodiment of the subject application, the histogram data is normalized by the number of pixels, as will be appreciated by those skilled in the art. The dominant spike regions of the calculated histogram data are then identified at step  1406  by the controller  108  or other suitable component associated with the document processing device  104 , the user device  114 , or the like. An N-sum value of the identified dominant spike regions is then calculated at step  1408 . The calculated N-sum value of the identified spike regions is then tested at step  1410  against a predetermined threshold value. Suitable examples of such a predetermined threshold value are discussed in greater detail above. The controller  108  or other suitable component associated with the document processing device  104 , the user device  114 , or the like then classifies the received image data at step  1412  as an artistic scene, a tinted artistic scene, or a sepia tone range artistic scene in accordance with the output of the testing performed at step  1410 . 
     Referring now to  FIG. 15 , there is shown a flowchart  1500  illustrating a method for artistic scene image detection in accordance with one embodiment of the subject application.  FIG. 15  is included herein for illustration and example purposes only, particularly with the selection of the 7-Sum determined value, and the skilled artisan will appreciate that other selected N-Sum values are capable of being used in accordance with the example method of  FIG. 14 . The methodology of  FIG. 15  begins at step  1502 , whereupon input image data such as a digital photograph, image, or the like is received by the controller  108  or other suitable component associated with the document processing device  104 , the user device  114 , or the like. It will be appreciated by those skilled in the art that the input image data is capable of being received from the user device  114  by the document processing device  104  via the computer network  102  from a portable storage device accessed by the document processing device  104  or the user device  114 ; via electronic communication to the document processing device  104  or the user device  114 ; via operations of the document processing device  104 , e.g., scanning, facsimile, etc.; or other means, as will be known in the art. Preferably, the received input image data is received as data encoded in a multi-dimensional color space such as, for example and without limitation, RGB, CMYK, CIE L*a*b*, YC b C r , YIQ, HSV, xyY, u′v′Y, L*u*v*, or the like. In accordance with one embodiment of the subject application, the input image data is capable of being received in any of a plurality of different electronic formats, as will be understood by those skilled in the art. Suitable examples of such formats include, for example and without limitation, JPEG, TIFF, RAW, PDF, BMP, GIF, or the like. 
     A determination is then made at step  1504  whether down-sizing of the received input image data is required. The skilled artisan will appreciate that such a determination is made by the controller  108  or other suitable component associated with the document processing device  104 , the user device  114 , or the like, based upon the computational costs associated with processing the received input image in accordance with the subject methodology of  FIG. 15 . Thus, when the received input image data corresponds to a large image file, e.g., high resolution, size, or the like, the controller  108  or other suitable component associated with the document processing device  104 , the user device  114 , or other such device then down-sizes the received input image file. Upon such a determination that down-sizing is required, flow proceeds to step  1506 . At step  1506 , the received image data is down-sized, as will be appreciated by those skilled in the art. Preferably, the down-sizing of image data corresponds, for example and without limitation, to the “blurring” and/or “down-sampling” of the received input image data. 
     Following down-sizing of the received image data or upon a determination that no down-sizing is required, flow progresses to step  1508 . At step  1508 , a determination is made by the controller  108  or other suitable component associated with the document processing device  104 , the user device  114 , or the like as to whether the received input image data requires conversion to HSV (hue, saturation, value (brightness)) color space. The skilled artisan will appreciate that, while the image data is capable of being received encoded in HSV color space, typical digital images are received in RGB or CMYK color space and, thus, require conversion in accordance with the subject application. Thus, when conversion is determined to be required, flow proceeds to step  1510 , whereupon the received input image data is converted to image data encoded in HSV color space. 
     Once HSV encoded image data has been obtained, operations proceed to step  1512 , whereupon near achromatic pixels in the received input image data are identified. The identified near achromatic pixels are then selectively discarded by the controller  108  or other suitable component associated with the document processing device  104 , the user device  114 , or the like at step  1514 . Those skilled in the art will appreciate that near achromatic pixels correspond to those pixels in an image having no color (achromatic) or those pixels that are almost achromatic. The identification and selective discarding of such near achromatic pixels are more adequately described in co-pending patent application Ser. No. 12/037,711, as referenced above. 
     At step  1516 , histogram data is calculated from the image data encoded in HSV color space. In accordance with one embodiment of the subject application, the histogram data is normalized in hue based upon the total number of pixels with all near achromatic pixels discarded. Dominant spike or peak regions are then identified from the calculated histogram data at step  1518 . The 7-Sum value of identified spikes or peaks in the histogram data is then calculated by the controller  108  or other suitable component associated with the document processing device  104 , the user device  114 , or the like at step  1520 . The use and calculation of the 7-Sum values associated with various spikes in the histogram data is addressed in greater detail above with respect to  FIGS. 4A-13 . 
     At step  1522 , the combined 7-Sum for the received image is then calculated at I max  and I max2 . The calculated combined 7-Sum value is then tested at step  1524  against a predetermined threshold value Th. In accordance with one example embodiment, the threshold values are optimized for automatic white balance and white stretch, i.e. fine-tuned in accordance with selected applications, such that the threshold value Th is 0.998, the threshold value Th′ is 0.9, and the threshold value Th″ is 0.5. A determination is then made at step  1526  as to whether the combined 7-Sum value falls within a pre-determined range of the threshold value, i.e. whether the combined 7-Sum value is greater than or equal to the threshold value Th. When the combined 7-Sum value is greater than or equal to the threshold value Th, flow proceeds to step  1528 , whereupon the received input image is classified as a tinted artistic scene image. Thus, it will be apparent to those skilled in the art that no automatic image correction is undertaken on the image by the associated controller  108  or other suitable component of the document processing device  104 , the user device  114 , or the like. Upon a determination at step  1526  that the calculated combined 7-sum value is not greater than or equal to the threshold value Th, flow proceeds to step  1530 . At step  1530 , a determination is made as to whether the combined 7-sum value is greater than a threshold value Th′, or whether the I max  value is greater than or equal to 1 but less than or equal to 18 (sepia (skin) tone range) and the combined 7-sum value is greater than a threshold value Th″. Upon a negative determination at step  1530 , flow proceeds to step  1534 , whereupon the received image is classified as a non-artistic scene, resulting in the performance of any suitable automatic image correction applicable to the received image data by the associated component of the document processing device  104 , the user device  114 , or the like. Upon a positive determination at step  1530 , flow proceeds to step  1532 , whereupon the received image data is classified as an artistic scene and, thus, no automatic image correction is undertaken on the received image by the user device  114 , the controller  108 , or other such component associated with the document processing device  104 . 
     The subject application extends to computer programs in the form of source code, object code, code intermediate sources and partially compiled object code, or in any other form suitable for use in the implementation of the subject application. Computer programs are suitably standalone applications, software components, scripts, or plug-ins to other applications. Computer programs embedding the subject application are advantageously embodied on a carrier, being any entity or device capable of carrying the computer program: for example, a storage medium such as ROM or RAM; optical recording media such as CD-ROM or magnetic recording media such as floppy discs; or any transmissible carrier such as an electrical or optical signal conveyed by electrical or optical cable, radio, or other means. Computer programs are suitably downloaded across the Internet from a server. Computer programs are also capable of being embedded in an integrated circuit. Any and all such embodiments containing code that will cause a computer to perform substantially the subject application principles as described will fall within the scope of the subject application. 
     The foregoing description of a preferred embodiment of the subject application has been presented for purposes of illustration and description. It is not intended to be exhaustive or to limit the subject application to the precise form disclosed. Obvious modifications or variations are possible in light of the above teachings. The embodiment was chosen and described to provide the best illustration of the principles of the subject application and its practical application to thereby enable one of ordinary skill in the art to use the subject application in various embodiments and with various modifications as are suited to the particular use contemplated. All such modifications and variations are within the scope of the subject application as determined by the appended claims when interpreted in accordance with the breadth to which they are fairly, legally, and equitably entitled.