Patent Publication Number: US-8542925-B2

Title: System and method to enable correction to application of substantially colorless material over identified text via segmentation

Description:
FIELD 
     This application generally relates to digital image processing, and in particular, to a system and method for identifying pixels representing text in printed documents to improve image quality. 
     BACKGROUND 
     Output devices, such as multi-function printers or devices (MFDs), are becoming quite complex and deal with sophisticated concurrent operations. During a print job or copy job, these devices may encounter problems while processing pixels of image data, including identifying all of the pixels representing more intricate details, such as text. This can affect image quality of the document when marking and outputting. 
     Such problems can occur when processed image data is sent for output. For example, each pixel of image data representing text may not be identified when page description language (PDL) image data is sent for rasterizing and output. The raster image may have mismatched text data (e.g., as compared to the electronic file) and can produce low density pixels marked on a page. 
     Moreover, some systems are configured to applying a clear coating over identified text pixels. However, if such pixels are not identified, and thus not coated, the printed or output document may resulting in skipped, hole ridden, rubbed off, and/or low quality text (e.g., due to failure to mark a pixel, or failure to cover a marked pixel, which can cause wear or removal of a marking). 
     SUMMARY 
     One aspect of the disclosure provides a processor-implemented method for processing image data using an image processing apparatus. The image processing apparatus has at least one processor for processing documents containing image data having a plurality of pixels. The method includes the following acts implemented by the at least one processor: receiving a page description language file of image data comprising a plurality of pixels and related image instructions; 
     raster image processing the page description language file to create a bitmap file with a first data structure indicating at least pixels representing text; 
     segmenting the bitmap file to determine at least pixels in the bitmap file representing text not indicated in the first data structure to form a second data structure, and 
     combining the first data structure and the second data structure to form a third data structure indicating locations for marking substantially colorless marking material onto a substrate using an image output device. 
     Another aspect of the disclosure provides a system for processing image data having a plurality of pixels. The system has at least one processing element with an input and an output and is configured to receive and process pixels of the image data. The at least one processing element is configured to: 
     receive a page description language file of image data comprising a plurality of pixels and related image instructions; 
     raster image process the page description language file to create a bitmap file with a first data structure indicating at least pixels representing text; 
     segment the bitmap file to determine at least pixels in the bitmap file representing text not indicated in the first data structure to form a second data structure, and 
     combine the first data structure and the second data structure to form a third data structure indicating locations for marking substantially colorless marking material onto a substrate using an image output device. 
     Yet another aspect of the disclosure provides a non-transitory computer readable medium having stored computer executable instructions, wherein the computer executable instructions, when executed by a computer, direct a computer to perform a method for processing image data, the method includes: receiving a page description language file of image data comprising a plurality of pixels and related image instructions; 
     raster image processing the page description language file to create a bitmap file with a first data structure indicating at least pixels representing text; 
     segmenting the bitmap file to determine at least pixels in the bitmap file representing text not indicated in the first data structure to form a second data structure, and 
     combining the first data structure and the second data structure to form a third data structure indicating locations for marking substantially colorless marking material onto a substrate using an image output device. 
     Other features of one or more embodiments of this disclosure will seem apparent from the following detailed description, and accompanying drawings, and the appended claims. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
       Embodiments of the present disclosure will now be disclosed, by way of example only, with reference to the accompanying schematic drawings in which corresponding reference symbols indicate corresponding parts, in which: 
         FIG. 1  illustrates a flow chart/block diagram illustrating a method for processing image data in accordance with an embodiment of the present disclosure; 
         FIG. 2  illustrates a schematic representation of implementing the method of  FIG. 1 , in accordance with an embodiment; 
         FIG. 3  illustrates a schematic representation of implementing the method of  FIG. 1 , in accordance with another embodiment; 
         FIG. 4  illustrates an exemplary method of segmenting the rasterized image data as indicated in  FIG. 1 , in accordance with an embodiment; 
         FIG. 5  illustrates an exemplary block diagram of an image path of a system, device, or image processing apparatus, in accordance with an embodiment, comprising at least one processor and an output device, for implementing the method of  FIG. 1 , in accordance with an embodiment, and 
         FIG. 6  illustrates a block diagram of a system, device, or image processing apparatus for implementing the method of  FIG. 1 , in accordance with an embodiment. 
     
    
    
     DETAILED DESCRIPTION 
     According to one or more embodiments, a methodology is disclosed that determines text pixels for marking and output using marking materials (e.g., ink, toner, or other marking medium having any type of colorant). The locations of the determined text pixels are used to determine pixels to be marked or covered with a substantially colorless or clear marking material. Because the colorless material coating can reduce or prevent wear or removal of marking material for a marked pixel, identification of text pixel locations for covering increases quality of the printed text pixels on a substrate. 
     This disclosure uses algorithms, methods, and processing elements (e.g., hardware) in multi-function systems/devices to determine text pixels taking the above into consideration, and identifies their locations to identify locations for marking substantially colorless marking material thereover. 
     Throughout this disclosure, the term “pixel” as used herein is defined as a pictorial element of data that may be provided in any format, color space, or compression state which is associated with or readily convertible into data that can be associated with a small area or spot in an image that is printed or displayed. Generally, a pixel is defined in terms of value (or brightness or intensity) and its position in an image. A pixel may be associated with an array of other small areas or spots within an image, including a portion of an image, such as a color separation plane. Accordingly, the term “pixel location” is also used interchangeably herein with the term pixel to represent a pictorial element of image data as defined above. An image generally comprises a plurality of pixels or pixel locations having a number of components that contribute to defining the image when it is either printed or displayed. 
     As used herein, “device dependent” color space (or image data) means color schemes which are tied to or related to color production by a machine, such as printer, scanner or monitor. Typical device dependent color spaces, for example, include red-green-blue (RGB) or cyan-magenta-yellow-black (CMYK) color spaces. The color gamut is produced by a machine using different combination of these colors. 
     On the other hand, “device independent” color space (or image data), as used herein, means color schemes which are not tied to color production of a machine. Typical device independent color spaces include, for instance, sRGB, CIE XYZ, YCbCr, and CIE (L*, a*, b*) color spaces. No device is needed to produce these colors. Rather, the color space is related to human observation of color. 
     Additionally, as used herein, an “electronic image” includes machine- or computer-readable data for electronically reproducing an image. It includes any electronic media content that is intended to be used in an electronic form or transmitted to a marking engine to be printed. In some instances, the electronic image may be an electronic document. As used herein, “electronic document” means any electronic media content that is intended to be used in an electronic form or printed output. Pixels in an electronic document may be formatted as Red-Green-Blue (RGB), cyan-magenta-yellow-black (CMYK), a device-independent color space (e.g., CIE-LAB, YCrCb, XYZ, etc.), or other pixel data formats. Conversions from one color space to another may also be possible, for instance, as known in the art. Pixels in an electronic document may be formatted, in some instances, as binary image data. Binary image data is single bit or bi-level, with only two possible values. More particularly, pixel values may be either ON (e.g., value=1) denoting an active pixel, or OFF (e.g., value=0) denoting background and/or no presence of marking or color. 
     Exemplary electronic documents may include various digital image, text, and mixed content files, such as PDF, TXT, DOC, TIFF, BMP, GIF, JPEG, and other common page description language (PDL) file and document formats, such as Adobe® Postscript®. A page description language (PDL) is a method of describing printed pages in a printer independent format. A PDL establishes an interface between a print driver or client and a print server or printer. No one standard PDL presently exists, and as a result a number of industry standards have emerged. Accordingly, it should be understood that reference to a PDL image file and/or document throughout this disclosure may include any of the above-mentioned examples, or any other page description language not mentioned above. 
     With any PDL or other electronic image format/document, there will inevitably be a step of translation of the PDL or image format data into a form usable by at least an image output terminal (IOT) or an output device, such as a printer, a copier, or an MFD. In accordance with an embodiment, such a step may be implemented through raster image processing (RIP), also known as ripping. Generally, when a document is to be printed, image data representing a document is input into a device and processed in an image path. For example, image data comprising a plurality of pixels is received and processed along an image path of a processor or system. In some instances, if the image data is not already in independent color space then a step of converting the image data to a device independent color space may be optionally performed. As the image data is processed, a determination may be made to determine if the input image data comprises different types of pixels, including text. During conversion of a PDL file, however, image quality problems can occur if text is not recognized (e.g., during ripping). In such cases, text pixels can be sent within the raster image, but can sometimes go unrecognized. If text pixels are not covered with a substantially colorless marking material (e.g., due to not being recognized as text pixels during processing), such pixels are prone to illegibility on an output document due to rubbing or rubbing off of color (or black) marking material that is applied to a page or sheet, e.g., during finishing and/or movement of a page or sheet through the machine. Accordingly, this disclosure describes a method for processing image data in order to more accurately identify pixels representing text (in an output document) so that image quality of the output document is improved. 
     In the detailed description below, reference is made to a determination of pixels representing text in an electronic image while processing image data for an output document. The determination of the text pixels is used to identify locations for applying or marking substantially colorless marking material over a pixel mark (i.e., the identification of the pixels themselves as being text pixels determines that the pixel should be covered with the colorless marking material). The determination/indication of text pixels as disclosed herein may be used for marking on a substrate as well, in order to identify all text pixels within the image data and to increase output image quality. 
       FIG. 1  is a flow chart/block diagram illustrating a method  100  for processing image data in accordance with an embodiment of this disclosure. The method  100  may be implemented by one or more processors or systems, such as those illustrated in  FIGS. 5 and 6  and further described below. It should be understood by one of skill in the art that image data of a page or document can be processed (along image path  500  in system  600 , shown in  FIGS. 5 and 6 , for example) before execution of the method  100 , although such processes are not discussed in detail herein. Method  100  comprises receiving a PDL file of image data comprising a plurality of pixels of image data and related image instructions at  102 . Such related image instructions include methods and details for outputting (e.g., printing) the image data, such as formatting, for example, and are not meant to be limiting. At  104 , the PDF file is processed using raster image processing (ripping) to create a bitmap file (which may comprise contone image data, for example). The bitmap file has a first data structure associated therewith indicating at least pixels representing text. At  106 , the ripped bitmap file is segmented to determine at least pixels in the bitmap file representing text that were not indicated, identified, or determined in the first data structure. Segmenting the ripped bitmap file is used to determine or form a second data structure. Then, as shown at  108 , the first data structure and the second data structure are combined to form a third data structure indicating locations for marking substantially colorless marking material onto a substrate (using an image output device). 
     Optionally, at  110 , the bitmap file (which includes information from the ripped image data) and the third data structure are sent to an image output device or image output terminal (IOT) for processing and output. At  112 , during optional use of the IOT or the output device, text pixels are marked on the substrate. In an embodiment, the text pixels may be marked using information indicated by the third data structure. For example, in one embodiment the third data structure indicates a determination of at least a combination of pixels that represent text (indicated or identified from both the ripped bitmap file and the segmentation process, per the first and second data structures). Thus, the information in the third data structure can be used (e.g., by a processor or output device) to correctly mark text pixels onto the substrate (e.g., using device parameters, at a predetermined density, etc.). 
     Additionally, as shown at  114 , the method  100  may further comprise an optional step of marking locations (using an output device/IOT) with substantially colorless marking material on the substrate using on the third data structure. That is, in an embodiment wherein the locations indicated in the third data structure correspond to text pixels, the third data structure may also indicate locations to mark substantially colorless marking material onto the substrate (e.g., over the text pixels), i.e., the third data structure can be used to determine such locations. In another embodiment, the third data structure directly indicates the locations to mark substantially colorless marking material onto the substrate. Thus, in accordance with either embodiment, after pixels are marked on the substrate with their marking material of any colorant(s), the pixel locations indicated in the third data structure can be covered, coated, or marked (over) with a substantially colorless marking material at  114 . 
     The “data structures” may be any type of electronic data associated with an electronic image data file that indicates elements and features of the image. The data structures may be configured to indicate feature(s) related to or associated with an image and/or its pixel locations through an identification or recognition process or algorithm. Any number or type of notation may be used, and the indication process is not limiting. For example, the data structures may be planes comprising information related to pixels. The planes may indicate a type of data a pixel location represents (e.g., type of pixel for output (text, background, contone)) using a binary format, e.g., YES or NO. Each plane may indicate ON and OFF pixel locations (e.g., in a binary format, e.g., one (1) being “ON and zero (0) being “OFF”) based on what that particular plane represents. 
     In accordance with an embodiment, data structures may be binary tag planes. That is, tags may be used to indicate that a pixel location represents (or does not represent) text when output. In an embodiment, tags are placed on pixel locations that represent text. In another embodiment, a plurality of types of tags are placed on each pixel location, with each tag indicating or identifying the type of data (e.g., text, background, text on tint) represented by the pixel location. In another embodiment, tags may be used to represent text pixels of a predetermined colorant. The type, number, and use of tags, however, is not meant to be limiting. 
       FIG. 2  illustrates an exemplary schematic representation of a method  200  for implementing the method  100  of  FIG. 1  using tag planes. As shown, PDL image data comprising a plurality of pixels and related image instructions is received/input at  202  and raster image processed, i.e., ripped, at  204 . As a result, a bitmap file with a first data structure indicating at least pixels representing text associated therewith is provided. A first data structure may be a font tag plane generated at  208  as a result of the ripping at  204 . For example, the font tag plane at  208  may be generated from the related image instructions received with PDL image data. The font tag plane is a binary tag plane indicating pixels as ON (e.g., one) or OFF (e.g., zero). In an embodiment, the font tag plane indicates pixels locations representing text as ON. The font tag plane may also include data or information for all colors/planes of pixels, e.g., C, M, Y, and/or K that represent text, for example. 
     The bitmap file generally indicates at least color planes for which pixel locations are associated therewith are also generated, as shown at  206 . In order to more accurately identify at least the pixels representing text in the document image data, the bitmap file of color planes (e.g., the CMYK planes) is processed using a segmentation method at  210 . Segmenting the bitmap file at  210  determines color planes for which pixel locations are associated therewith, as shown at  216 , as well as at least those pixels in the bitmap file representing text not indicated in the first data structure. As a result, a second data structure in the form of a text tag plane is formed at  212 . The text tag plane may, however, determine similar pixel locations determined in the first data structure, i.e., the font tag plane determined at  208 . In accordance with an embodiment, the text tag plane indicates all pixel locations that represent text. The text tag plane is a binary tag plane indicating pixels as ON (e.g., one) or OFF (e.g., zero). In an embodiment, the text tag plane indicates pixels locations representing text as ON. 
     The results from the font tag plane and text tag plane are then combined at  214 . An “OR” process for the two tag planes is implemented at  214  to determine the pixel locations indicating text. So, for example, if one plane indicates that a location is text, then the OR process indicates the location as text in the combined data structure or plane. The combination of results resulting from the “OR” process increases the accuracy of the determination of (at least) text pixels in the document by combining the determinations of the two planes at  208  and  212 . Accordingly, in an embodiment, as a result of the combination a third data structure in the form of a comprehensive tag plane is formed at  218 . The comprehensive tag plane is a binary tag plane indicating pixels as ON (e.g., one) or OFF (e.g., zero). In an embodiment, the text tag plane indicates pixels locations representing text as ON (e.g., a value of one (1) indicates the presence of a text pixel and zero (0) corresponds to no font detected for the pixel). 
     In an embodiment, the comprehensive tag plane may be the font tag plane of  208  that is altered and updated to include the results of the text tag plane. For example, for pixel locations where segmentation at  210  determines that text is resident, tags will be added (if not already present due font tagging described above) to the comprehensive tag plane. 
     Thereafter, the segmented color planes at  216  and the comprehensive tag plane at  218  may be sent for output (e.g., to an output device/IOT) for output processing. In accordance with an embodiment, the tags of the comprehensive tag plane indicate to the output device all pixel locations representing text in the image data. Thus, the comprehensive tag plane also indicates locations for marking substantially colorless marking material on the substrate, since the herein disclosed method is configured to use a marking device/output device to mark substantially colorless marking material over the text pixels. As shown at  220  in  FIG. 2 , the output device/IOT may be configured to determine locations of text pixels based on the comprehensive tag plane. Based on that determination, the output device/IOT determines locations for marking substantially colorless marking material onto the substrate (e.g., over the text pixels), using a marking device, after the marking of pixels on the substrate. 
     The determination of locations for marking substantially colorless marking material and the utilization of data by the output device/IOT may be implemented in any number of ways, however. As noted with respect to  FIG. 2 , the text pixels can be determined upstream of the IOT, and the IOT can be used to determine the locations. In another embodiment, the locations may be determined upstream (e.g., by a processor or DFE) before being sent to the IOT.  FIG. 3  illustrates an alternate method  300  for implementing the method  100  of  FIG. 1  using tag planes. In accordance with an embodiment, the method  300  is implemented in a system that is capable of combining a RIPped determination for the application of substantially colorless marking material on the output document with a determination for application of the substantially colorless marking material over text pixels determined through segmentation. The RIPped determination may include a determination of pixels representing text, for example, and/or other pixels that may benefit from application of substantially colorless marking material after marking on a document. Accordingly, the system can implement the method to ensure that at least text pixels are recognized and configured for marking with colorless marking material when output. The disclosed method can assist in improving and/or correcting application of substantially colorless marking material in existing systems capable of analyzing data and applying marks or a coating to one or more selective parts of the image. 
     As shown, PDL image data comprising a plurality of pixels and related image instructions is received/input at  302  and raster image processed, i.e., ripped, at  304 . As a result, a bitmap file with a first data structure indicating at least pixels representing text associated therewith is provided. A first data structure may be a font tag plane generated at  308  as a result of the ripping at  304 . As noted above, the font tag plane at  308  may be generated from the related image instructions received with PDL image data and is a binary tag plane indicating pixels as ON (e.g., one) or OFF (e.g., zero). In an embodiment, the font tag plane indicates pixels locations representing text as ON. The font tag plane may also include data or information for all colors/planes of pixels, e.g., C, M, Y, and/or K that represent text, for example. 
     The bitmap file generally indicates at least color planes for which pixel locations are associated therewith are also generated, as shown at  306 . The bitmap file may also include information related to pixels for marking with substantially colorless marking material. For example, the information may be in the form of a clear plane that indicates if there should be application of substantially colorless marking material to pixels (such as text pixels). The application of the substantially colorless material may have a tonal value, much like the application of marking material or colorant. For example, a pixel can have an 8-bit value comprising 256 tones or shades in the image. In a similar manner, the clear plane can indicate a location associated with a pixel that is determined to be covered with substantially clear marking material comprising one of 256 values (i.e., 0 to 255). The RIPped clear plane can indicate a selected value. However, as previously noted, this initial RIPping and determination may miss or pass pixels that represent text and/or should be covered in substantially colorless marking material. In order to more accurately identify at least the pixels representing text in the document image data, the bitmap file of planes (e.g., the CMYK planes) is processed using a segmentation method at  310 . Segmenting the bitmap file at  310  determines and/or forwards the color planes for which pixel locations are associated therewith and a clear plane, as shown at  316 , as well as at least those pixels in the bitmap file representing text not indicated in the first data structure. As a result, a second data structure in the form of a text tag plane is formed at  312 . The text tag plane may, however, determine similar pixel locations determined in the first data structure, i.e., the font tag plane determined at  308 . In accordance with an embodiment, the text tag plane indicates all pixel locations that represent text. The text tag plane is a binary tag plane indicating pixels as ON (e.g., one) or OFF (e.g., zero). In an embodiment, the text tag plane indicates pixels locations representing text as ON. 
     The results from the font tag plane and text tag plane are then combined at  314 . An “OR” process for the two tag planes is implemented at  314  to determine the pixel locations indicating text. So, for example, if one plane indicates that a location is text, then the OR process indicates the location as text in the combined data structure or plane. The combination of results resulting from the “OR” process increases the accuracy of the determination of (at least) text pixels in the document by combining the determinations of the two planes at  308  and  312 . Accordingly, in an embodiment, as a result of the combination a third data structure in the form of a comprehensive clear plane is formed at  318 . The comprehensive clear plane is a binary tag plane indicating locations for marking substantially colorless marking material on the substrate. The locations for marking such material can be determined (e.g., by a processor or engine) using at least the combined text pixel location results of the font tag plane and text tag plane. The comprehensive clear plane can indicate a location as either ON (e.g., one) or OFF (e.g., zero). In an embodiment, the comprehensive clear plane indicates locations for marking substantially colorless marking material as ON (e.g., a value of one (1) indicates a corresponding location of a text pixel and zero (0) corresponds to a location of a pixel that does not represent text). 
     As previously mentioned, in an embodiment, the clear plane can include a value or level including and/or between 0 to 255, indicating an amount of substantially colorless marking material to be applied to a location of a pixel. For example, a zero value (0) would indicate that no substantially clear marking material is applied to the location (e.g., on the paper or document), and a value of 255 would indicate that the location is substantially fully covered with substantially clear marking material. Accordingly, in order to combine the binary results of the comprehensive clear plane at  318  with those determined during RIPping (e.g., noted at  306  and passed to  316 ), the binary results need to be converted. At  320 , a clear plane is converted from binary such that its information can be combined with the contone content determined during RIPping. In the binary comprehensive clear plane, if a location of pixel has a value of zero (0), the location is given a value of zero (0) in the contone clear plane at  320  and it is indicated as OFF (i.e., the location does not correspond to a text pixel). If a location of a pixel in the binary comprehensive clear plane has a value of one (1), then it is given a value of 255 in the contone clear plane at  320  and it is indicated as ON (i.e., the location corresponds to a text pixel and should be substantially fully covered with substantially colorless marking material). 
     Thereafter, the segmented color planes and clear plane at  316  (i.e., the bitmap file) and the resulting contone clear plane at  320  are further combined at  322  to determine a fourth data structure indicating locations for marking substantially colorless marking material onto a substrate using an image output device. The fourth data structure is a resultant clear plane determined from the combination of the clear plane data found during RIPping and the combined clear plane data resulting from segmentation. At  322 , an “OR” process for the two planes is implemented to determine the resultant clear plane at  324  (indicating pixel locations of text to be marked) which can be sent from the processor(s) (DFE) to the output device (IOT) with the color (e.g., CMYK) planes indicating marking of other color(s) for the image pixels. In an embodiment, the value that is higher in either the clear plane from  316  or the clear plane from  320  is used to indicate the value of the substantially colorless marking material to be applied to the associated pixel location of the resultant clear plane at  324 . So, for example, if the clear plane from  320  indicates that a location has a value of 255, and the clear plane at  316  indicates a location corresponding to that pixel location is  200 , then the OR process indicates the location has a value of 255 in the resultant combined data structure or plane at  324 . Such an example, however, is not meant to be limiting. The combination of results resulting from the “OR” process increases the accuracy of the application of substantially colorless marking material to (at least) text pixels in the document by combining the determinations of the two planes at  306  (or  316 ) and  320 . 
     However, it should be noted that, in accordance with an embodiment, the resultant clear plane at  324  may comprise a binary tag plane either indicating YES or NO locations for marking substantially colorless marking material thereon. That is, the clear plane can indicate a location as either ON (e.g., one) or OFF (e.g., zero), with or without application of substantially colorless marking material, without a value of application of the marking material associated therewith. 
     After the color planes and resultant clear plane are determined at  324 , they may be sent for output (e.g., to an output device/IOT) for output processing. At  320 , the output device uses the tags of the clear plane to mark (with a marking device/output device) substantially colorless marking material over the text pixels. 
     Accordingly,  FIGS. 2 and 3  show that in the herein disclosed methods the output device/IOT may be configured to either process a received comprehensive tag plane representing text pixels to determine the locations for marking substantially colorless marking material, or process a clear tag plane that indicates the locations for marking substantially colorless marking material (e.g., the locations can be determined by a processor when combining the results at  314  before sending to the output device/IOT). 
     The method for segmenting the ripped bitmap file at  210  and/or  310  should not be limiting. Any number of known or future methods for segmenting image data may be implemented by this method. In an embodiment, the segmentation technology implemented by the processor(s) is an auto-windowing segmentation technique, configured to use a 2 pass methodology for analyzing pixels of image data by segmenting pixels/regions into classifications such as text, continuous tone, background, different halftone frequencies and text on tint classifications. The segmentation parameters can be tuned to the “clean” signal that the ripped image produces. As an example, one or more similar methods as disclosed in U.S. Pat. No. 6,347,153 B1 to Triplett et al., issued on Feb. 12, 2002, U.S. Pat. No. 6,181,829 B1 to Clark et al., issued on Jan. 30, 2001, U.S. Pat. No. 5,296,430 to Shiau et al., and U.S. Pat. No. 7,844,118 B1 to Li et al., each of which are assigned to the same assignee (Xerox Corporation) and are incorporated by reference in their entirety herein, may be used as a segmentation technique that is applied to the ripped bitmap image data. Accordingly, any number of methods may be used for the determination of the text tag plane at  212  and/or  312 . 
     In an embodiment, segmentation is applied to the raster (ripped) image before (xm2) compression. 
     As shown in  FIGS. 2 and 3 , the processing of the image data (including ripping and segmentation of the ripped image data) may be performed by one or more processing elements that are part of a device or system. In an embodiment, a print engine  201  or  301 , which may include a print driver or print controller, produces a PDL file at  202  or  302  and processes it as shown from  204 - 218  or  304 - 322 . More specifically, the print engine is noted as a digital front end (DFE) (i.e., processor(s)), which is typically used for processing the image data to generate an image. In an embodiment, the print engine/DFE  201 / 301  can implement the ripping and segmentation of the image data, as well as generation of the comprehensive tag plane for black text, and send both the processed image data and comprehensive tag plane to the output device/IOT for output (e.g., printing). The processor(s) or modules included in the DFE are not limiting. Further details regarding processing of the image data along an image path and an exemplary system are described below with reference to  FIGS. 5 and 6 , respectively. 
     Above it is noted that the output device is configured to mark over text pixels using substantially colorless marking material (e.g., see  220  in  FIG. 2 ). The material may be marked over the pixel after the determined color(s) of the pixel are marked, for example. In another embodiment, the material may be marked after all color(s) are marked. For example, the clear tag plane may act as a template for marking the substantially colorless marking material over the pixels after the substrate has been marked with the image data. 
     It should also be understood that processing techniques performed by the IOT for marking and printing on a substrate that may take place for compatibility purposes, according to IOT settings, and the like. In an embodiment, the IOT may be configured to adjust the colorant content and density setting (of the marking material) for pixels (e.g., text pixels, pixels representing background, text on tint, etc.) so that the resultant output on the substrate will still yield high output image quality using the IOT, in addition to higher quality output text pixels. 
     With regards to a method for determining, for example, pixel locations that represent text pixels, and thus locations for marking substantially colorless material, any number of methods may be used.  FIG. 4  illustrates one method that may executed as a segmentation technique at  106  in method  100  and configured to be implemented by a processor to determine at least text pixels in image data for the text tag plane (e.g., at  212  or  312 ) (or second data structure). 
     At  400  the ripped bitmap file is received. Then, at  402 , for each pixel location, it is determined if a pixel in the image data is a text pixel (e.g., using a segmentation technique, as noted above). If it is not a text pixel, i.e., NO, then the pixel location is indicated or marked (e.g., via a tag) in the second data structure at  406  as OFF (e.g., zero value). 
     If, however, at  402  it is determined that the pixel is a text pixel, i.e., YES, then the pixel location is indicated or marked (e.g., via a tag) in the second data structure as ON (e.g., value of one). 
     After the indication/marking at  404  or  406 , then at  408  the next pixel location is selected and then processed, beginning at the determination at  402 . The method continues until all pixel locations are processed. 
     In accordance with an embodiment, any of the noted embodiments and implementations shown in  FIGS. 1-4  may be implemented for a particular marking color or combination of colors. For example, for a CMYK marking device, the processor and/or system may be configured to determine black only (e.g., pure black (K)) text pixels for marking and output using the above described methods and implementations, and, for black only pixels, marking or covering said black pixels with substantially colorless marking material. In another embodiment, the processor and/or system may be configured to determine text pixels using the above described methods and implementations for those text pixels with only cyan marking material, only magenta marking material, or only yellow marking material. Accordingly, in either embodiment, such indications may be made in the second data structure (e.g., tag plane) and combined with the ripped image data (into the third data structure) for output. In another embodiment, the output device/IOT may be configured to determine pixel locations representing text of one or more particular colors, and may be configured to mark such pixels on a substrate without adjustment (e.g., at a predetermined density). 
     In some embodiments, the above-described features of method  100  (including segmenting ripped image data) may be optionally implemented or requested by a customer for a specific device or system by selection (e.g., using a user interface (UI) or manual switch). It may be implemented locally (at the machine) or remotely (through a network). For example, the customer or user may be prompted to invoke application and use of the method  100  in  FIG. 1 , or request use of method  100  (e.g., for a particular document, or for a particular device) before printing a document or before using the device. In an embodiment, for a machine that is configured to implement the method  100 , the machine may have the described ripped segmentation shown in method  100  in a default “OFF” state (e.g., due to potential performance degradation and considerations). When a customer or user wishes to process his/her document/image to enable correction and/or improvements to image quality by applying substantially colorless material over text, the user may implement the method  100  by selecting (or switching) the setting of the machine. In another embodiment, the switch or selection to implement the method  100  may be available to operator(s) or supervisor(s) for a particular machine or server. 
     This feature as described by the method  100  can improve customer satisfaction with output documents. For example, it can improve changes to the electronic image in cases when text is inserted, or modified (e.g., as bit maps for reasons such as last minute corrections at bit map level), or when secure or legal text is inserted into the document, and the like. Generally, because it segments the raster image to determine any missing pixels that represent (black) text, the marked image has increased accuracy and output quality. Accordingly, problems such as skip pitches and holes in output text are reduced. 
     In some cases, processing of each job using method  100  may require more of the image data to be RIPped ahead before commitment to print, depending on the type of machine or device used for output. The number of sheets that may needed to be RIP processed before commitment to print a particular document can be raised. The change (delta Δ) in sheets that are raster image processing can be determined through testing, for example. 
       FIG. 5  shows an example of a block diagram of a multifunction image path  500  used to handle concurrent operations for an image processing apparatus. More specifically, image path  500  is representative of one or more paths through which image data of an input document  502  or page, input into an image processing apparatus, may be processed using a plurality of processing elements (or modules) and then output. An example of such an apparatus may be a MFD, for example. The image path of the image processing apparatus or device comprises, among other devices, an image input terminal (IIT)  504 , a processor or processing elements  506  and  510 , a memory  509  and/or a storage device  511 , and an image output terminal (IOT)  512  and/or marking engine interface (also referred to as a print engine). Generally, these elements (as will be generally described) of the device are provided to perform functions that assist in receiving image data such as a scanned document, configuring the image path of the processing elements  506  and  510  to process the image data, and outputting the image data. The image processing apparatus can comprise a plurality of image paths for manipulating image data of a document for output. One example includes printing a document using a print driver  518  according to a selected output mode of the image processing apparatus. However, it should be noted that the apparatus or device may comprise additional elements not described herein or alternative elements for performing similar functions, and should not be limited to those elements as illustrated in  FIG. 5 . Generally, the image path shown corresponds to any number of output modes that may be selected for an image processing apparatus. Further, with the herein disclosed method, existing image paths may be easily altered. For example, modules for implementing segmentation may already exist in the image path, or a separate segmentation module may be added to the image path for implementation after raster image processing of an input document, if so desired. The illustrated multifunction image path  500  for processing an electronic image is not limiting. 
     The IIT  504  is used to scan or acquire an input document or page into image data to be processed along the multifunction image path  500 . The IIT  504  may be a digital scanner, for example. The scanner may capture image data as binary or contone image data. Generally, however, any device used to scan or capture the image data of a document is regarded and will be referred to as an IIT. For example, the image data may be captured by a scanner in a copier, a facsimile machine, a multi-function device, a camera, a video camera, or any other known or later device that is capable of scanning a document and capturing electronic image data. In some embodiments, IIT  504  may be connected to a network or telephone system, for example, to receive as input image data such as via a facsimile (fax) machine or computer (CPU). Input documents and/or image data may be received via a telephone number, an e-mail address, an Internet Protocol (IP) address, a server, or other methods for sending and/or receiving electronic image data. 
     A processor or plurality of processing elements  506 ,  516  and  510  for processing and/or manipulating image data using a plurality of operations and/or processes are also provided in the image paths. The description of the processing elements below provides an example of devices capable of implementing processes to be performed and should not be limiting. For example, additional processing elements may be provided along the image path  500 . Alternatively, additional operations may be performed on the image data other than or in addition to those described with reference to  FIGS. 1-4 . 
     The multifunction image path  500  may comprise a plurality of image processing elements (or processors) and for manipulating image data received from the IIT  504  or other input devices using a plurality of operations and/or processes. The processing elements and may be a combination of image processing elements which comprise software and hardware elements that perform a number of operations on the image data received from the IIT  504  (or other source) using a set of parameters. The parameters are used to convert the images to the format desired as output (e.g., high quality) along the image path. The processing elements may be a part of a computer system or apparatus such as a xerographic system, a photocopier, a printing device, or MFD. For simplicity purposes, the term “processing element” throughout the application will refer to one or more elements capable of executing machine executable program instructions. It is to be understood that any number of processing elements may be used and that additional operations or processes besides those described below may be provided in an image path. 
     More specifically, the multifunction image path  500  comprises a front end processing element  506 , a memory  509 , storage  511 , and a back end processing element  510 . The front end processing element  506  is an image processing element that receives image data from the IIT  504  and is used to process the image data according to user preferences such that it may be stored and later retrieved for output. The back end processing element  510  is generally used at the end of an image path to retrieve stored image data (e.g., from memory  509 , storage  511 , or system memory  514 ) and to process the image data such that the image data may be output to a printing device as an accurate recreation of the original input or scanned image. Of course, processing elements may also be used for compression and/or decompression of image data. 
     Each of the image processing elements comprises an input and an output. Additionally, the system or apparatus may also include one or more controllers or routers (not shown) to select and route the image data between the processing elements  506  and  510  and memory  509 , storage  511 , and/or storage  514 , for example. 
     Front end processing element  406  receives as input the image data from the IIT  504  and processes the image data along the image path. Front end processing element  506  may be used to process the image data as well as determine user-defined operations generally known in the art. For example, the front end processing element  506  may be used for color space conversion, reduction or enlargement, document registration, and/or performing other operations or processes on the image data. 
     Memory  509  and/or storage  511  may be used to store image data. For example, memory  509  and/or storage  511  may be used to temporarily store the original image data of document input via IIT  504 . Converted (e.g., contone to binary image data) or compressed image data may also be stored in the memory  509  and/or storage  511 . Memory  509  and/or storage  511  may be used to store machine readable instructions to be executed by the processor/processing elements. The memory  509  and/or storage  511  may be implemented using static or dynamic RAM (random access memory), a floppy disk and disk drive, a writable optical disk and disk drive, a hard disk and disk drive, flash memory, or the like, and may be distributed among separate memory components. The memory  509  and/or storage  511  can also include read only memory, or other removable storage drive(s) or memory devices. Additional description regarding computer or machine readable instructions and medium is described below with respect to  FIG. 6 . 
     System memory  514  may also be considered a main memory of the image processing apparatus. System memory  514  is used to run software associated with a controller, for example. System memory  514  may comprise, for example, a hard disk and drive which includes programs, image data, and the like that may be used for processing, etc. In some embodiments, system memory  514 , memory  509 , and/or storage  511  may be interchangeable or provided as a single device. 
     Generally, also associated with memory  509  and storage  511  is a device or program that is capable of encoding and decoding image data. For example, the image data may be processing by a plurality of coder-decoder pairs, i.e., CODEC, which is generally known in the art. Codec may be provided to perform any number of compression/decompression techniques on the image data including, but not limited to JPEG or JBIG2. A compressor and decompressor may use compression/decompression algorithms or other encoding/decoding methods, and should not be limiting. 
     The front end processing element  506  may communicate with memory  509  and/or storage  511  to store processed and/or compressed image data, for example. Compressed image data may be stored in memory  509  and/or storage  511  temporarily or for a later time when needed. When the image data is needed or it is time for marking (e.g., using the marking engine interface/IOT  512  or printing device), the image data may be retrieved from memory  509 , storage  511 , and/or storage  514  via the back end processing element  510  to be exported, for example. 
     In some embodiments, the multifunction image path  500  may also include a middle functions processing element  516  which may be used to perform some additional image data manipulation. Middle functions element  516  may be used for middle function operations including, but not limited to, rotation, annotation, and merging, and for compressing and/or decompressing image data for output, for example. The middle functions processing element  516  may communicate with memory and/or storage to store processed and/or compressed image data, for example. The input and output of image data to the middle functions processing element  516  depends on the selectively chosen image path or output mode. In some embodiments, middle functions processing element  516  may receive and store image data in PDL format or intermediate image format (IIF). The middle functions element  516  may also process and format image data for exporting out on a network, such as PDF, TIFF, or JPEG file formats, or for a fax device. Nonetheless, the functions performed by middle functions processing element  516  should not be limiting. 
     Back end processing element  510  receives processed image data retrieved from the memory  509  or storage  511 . Back end processing element  510  may be used to further render the image data for output. For example, back end processing element  510  may be used to convert the color space of the processed image data (e.g., convert from device independent color space such as standard RGB (sRGB) or CIE L*a*b color space to device dependent CMYK color space), provide color balance, further rendering, filtering, and/or other operations or processes to prepare the images for marking. Subsequently, the back end processing element  510  may be used to decompress the image data and output the image data to the IOT  512 . The output of processed image data from the back end processing element  510  depends on the image path or selected output mode. 
     In an embodiment, the processed image data may be directly output to the marking engine interface or IOT  512  for printing using a printer/MFD. The IOT  512  or marking engine interface may be associated with a printer or MFD which is used for printing documents. The IOT or marking engine interface is used to output the processing image data to the printer for a copy or print job. The IOT  512  or marking engine interface may further perform image processing on the image data to make corrections or compensate for deviation in the printing process. Alternatively, the back end processing element  510  may be used to perform further image processing on the image data. 
     The IOT  512  outputs processed image data to the printer or apparatus to complete the scan image path, for example. Of course, the algorithms and processes used by the elements in the image path shown in  FIG. 5  should not be limiting. Any number of data compression algorithms (e.g., lossless, lossy), decompression algorithms, color conversion algorithms (e.g., contone to binary, binary to grayscale, etc.) and the like may be performed to provide a high quality output document  513  (in addition to the method  100  of  FIG. 1 ). 
     With regard to a print image path implementing the method  100  of  FIG. 1 , one possible print operation comprises a print driver  518  (also referred to as a print controller). Documents may be sent to print driver  518 , for example, through a network interface and/or user interface (UI). The print controller  510  accepts content for digital images desired to be printed in any one of a number of possible page description language (PDL) formats. The print driver  518  is used to manage print devices, e.g., color laser printers, production printers, and digital presses, especially in high-volume environments. The print controller  510  may be a part of the printing device itself or an external device, such as a personal computer (PC) or server, or other digital device comprising software, that interfaces to a network and will accept image content and process the image content for copier or printer devices. In one embodiment, the print driver  518  may be a digital front end (DFE). Printer driver  518  produces a PDL (Page Description Language) file  520  for printing via an IOT  512 . Printer controller  518  may interpret, convert or, in some cases rasterize input print data (if a raster image processor is included therein) in the form of a page description language (e.g., PostScript, PCL), markup language (e.g., XML) or other special document format or language into a formatted language or instructions that IOT  512  can understand. 
     The PDL file is processed by a Raster Image Processing element (RIP)  522  to produce formatted image data capable of being further processed before compression and marking. The RIP  522  may be located within an output device itself or externally implemented as hardware, software, or a combination. As an example, RIP  522  may be implemented in a software application or device driver. A RIP  522  may also reside within printer driver  518 , in an embodiment. Examples of raster image processing operations may include image and graphics interpretation, rasterization, scaling, segmentation, color space transformation, image enhancement, color correction, halftoning, compression etc. 
     Typically a ripped image is used for rendering by a print engine or IOT  512 . However, in accordance with this disclosure, the ripped image is further processed to produce at least greater image quality of text in the output document. Specifically, the pixels of ripped image data are processed using method  100  in  FIG. 1  to classify and/or determine pixels representing text in the output document. After processing via method  100 , the electronic image data can be compressed for storage in the system memory  514 , storage  511 , and/or memory  509 , before being output for marking to IOT  512 . 
     Then, the input to the IOT  512  is a rasterized bitmap file that is generated by a combination of the raster image processed image data (which may include any related instructions) and results of the subsequent segmentation performed on the image data (e.g., see  FIG. 2 ). The IOT  512  may further perform image processing to make corrections or compensation to correct for deviations in the printing process and/or to determine locations for marking with substantially colorless marking material (as per the method of  FIG. 2 ). 
     Generally, any suitable printing apparatus may be employed to implement method  100  and to comprehensively identify text pixels and mark substantially colorless marking material over the text pixels in a document. The marking materials of this disclosure can be used in or applied by an image processing apparatus configured to generate an ink-based (e.g., solid ink) or toner-based image on a substrate. For example, the printing apparatus may be a machine that incorporates a plurality of marking material applicators, stations, or housings, such that color marking materials (e.g., cyan, magenta, yellow, and black, or CMYK) may be housed therein for application to the substrate. Moreover, the applicators, stations, or housing may include at least one supply of substantially colorless marking material, as described below with reference to  FIG. 6 . Its housing may be in addition to or in replace of one or more other marking material applicators. 
     The herein described embodiments may be used in inkjet device, such as, for example, a solid inkjet printer, an aqueous inkjet printer, or a UV inkjet printer, or they may be used in an electrophotographic printing system or a lithographic printing system. 
     For explanatory purposes only,  FIG. 6  is a block diagram illustrating an exemplary printing apparatus  600  that may be used in accordance with an embodiment for outputting documents processed using the method  100  of  FIG. 1 . The illustrated elements of apparatus  600  of  FIG. 6  may be a part of a computer system, device, or apparatus such as a xerographic system, a photocopier, a printing device, or a multi-function device (MFD). In an embodiment, the apparatus  600  may be a phase change or solid or UV-cured ink jet printing system, or electrophotographic printing system. 
     For example, the apparatus  600  may comprise an image capture device  602 , at least one processor  604 , a controller(s)  606 , memory  608  and/or storage  610 , marking devices  612 , and an output device  614 . Each of the devices shown in system  600  may also be considered modules, and, therefore, the terms “device” and “module” are used interchangeably herein. The devices or modules illustrated in  FIG. 6  (further described below) are not meant to be limiting. It is to be understood that any number of elements or modules may be used (e.g., more or less modules may be used and/or combined) and that additional operations or processes besides those described below may be provided.  FIG. 5  (described above) illustrates an exemplary image path for processing image data according to method  100  using such devices or modules, which may be included in system  600 . 
     Generally, some of devices or modules shown in  FIG. 6  are known by those of skill in the art and are therefore not discussed in great detail herein. Moreover,  FIGS. 5 and 6  show similar devices and it should be understood that the above description for the features in the image path of  FIG. 5  applies to the features in  FIG. 6 . The features in  FIG. 6  are designed to show a system incorporating the basic elements used to process and mark the image data (e.g., through an image path  500  as shown in  FIG. 5 ). 
     For example, the image capture device  602  is configured to provide and/or receive image data, much like the described input device or IIT  504 . At least one processor  604  or processing element is configured to process pixels of the image data in order to process image data for output. Controller  606  may be used to direct or control any number of modules or devices in system  600 . The at least one processor  604  may be instructed by one or more controllers  606  to process the image data that is provided or received. The processor or processing element may be a combination of image processing elements or modules which comprise software and hardware elements that may perform a number of operations on the image data received from the image capture device  602  using a set of parameters (e.g., processors  506 ,  516 , and  510  of  FIG. 5 ). The parameters may be used to convert the images to the format desired as output (e.g., high quality) along an image path. 
     When images are called for marking, they may be called out of memory  608  or storage  610  and subsequently processed and/or decompressed. A decompressor  612  may be used to restore the compressed data using any algorithm for reversing the used compression algorithm, so that the image data comprises the segmented and ripped image data and comprehensive/clear tag plane information. 
     An output device  614  may be provided to optionally output the image data (e.g., as noted in the method  100  at  112 ) (upon cue). Output device  614  may be any type of device that is designed to output the image data, e.g., IOT  512 . In an embodiment, the output device  614  may decompress the image data and information before output. In some embodiments, decompressor  612  is provided in output device  614  of system  600  to decompress image data before outputting the image data with output device  614 , if needed. The decompressor  612  and output device  614  may be the same module, or separate modules. 
     The marking devices  616  and  618  are applicators, stations, print-heads, or housings incorporated into the output device  614  of the apparatus  600  used to mark or apply marking materials. For example, marking devices  616  can be used to mark color (CMYK) inks for printing image data of a document and marking device  618  can be used to mark substantially colorless marking material over at least the indicated or identified text pixels of a document. In an embodiment, controller  606  is used to control one or more marking devices or applicators  616  and/or  618  of system  600 . Any number of marking applicators  616 ,  618  may be used. 
     With regards to the substantially colorless marking material, it should be understood that application of the material onto the substrate and over indicated text pixels is not meant to limit visibility of the marked image/text pixels. Rather, as noted above, it is intended to maintain integrity of the ink/toner that is applied to the substrate. Additionally, by applying substantially colorless marking material to identified text locations (as opposed to an entire page, for example), less material is used and therefore this disclosure further reduces costs associated with printing. 
     The marking material used for application over the identified text pixels is substantially colorless. In an embodiment, the marking material may be at least colorless to light having wavelengths within the visible spectrum. As used throughout this disclosure, a substantially “colorless” marking material is defined as a material that is substantially free of any colorants such as pigments or dyes, which give the other inks/toners their characteristic color properties in the visible range. This is because the marking material is used as an overcoat and applied over printed pixels of image data on the substrate (e.g., overcoats on ink based images and xerographic images), to allow for printed image data to still be viewed through the marking material. 
     The substantially colorless marking material may or may not be visible to the naked human eye. The “naked human eye” refers to human visual perception that is unaided by a light-discerning or light-collecting optical device. It is envisioned that in some instances, the marking material could be used as a security mark for identification or authentication purposes. The medium could also be configured, in some embodiments, to be substantially visible to a machine when the medium is illuminated by visible or non-visible light. The “machine” refers to a device that is used to distinguish or discern a security mark. In an embodiment, a machine (e.g., a scanner) may include a light source. In another embodiment, a machine (e.g., a camera) may be aided by a light source (e.g., laser or radiation source). The machine can be a part of a printing system, such as system  600 , or a separate device. The medium may be an “active” marking material, i.e., a marking material that is configured to substantially react to radiation having at least some wavelengths outside a visible spectrum, such that the mark is distinguishable by the human eye or by a machine when exposed to such radiation. 
     The gloss value of the marking material can be of any value (e.g., as measured by a gloss meter) and is not meant to be limiting. In an embodiment, the gloss of the marks over the printed image data is substantially similar or the same as that of the substrate. In some embodiments, the marking material can have a gloss appearance that is different from that of a default paper or substrate used in a printing apparatus. Also, the substrate on which the marking material is applied may comprise a matte or a glossy surface and is not meant to be limiting. 
     Referring back to  FIG. 6 , the processor  604 , marking device(s)  616  and/or  618 , and/or other associated modules of the apparatus  600  illustrated in  FIG. 6  may be used to perform or implement the non-limiting steps  102 - 114  as described in method  100  of  FIG. 1 , for example. These steps may or may not include the implementations illustrated in  FIGS. 2 ,  3  and  4 . The system  600  may also process image data using modules shown in the image path  500  of  FIG. 5 . 
     As briefly mentioned above, other embodiments include incorporating the above methods into a set of computer executable instructions readable by a computer and stored on a data carrier or otherwise a computer readable medium, such that the method  100  (in FIG.  1 )—as well as method  200  and  300 —is automated. In a possible embodiment, the methods may be incorporated into an operative set of processor executable instructions configured for execution by at least one processor.  FIGS. 1-4  show flow charts of such computer readable instructions that may be implemented by one or more processing elements/processors. The methods shown in the Figures may be implemented by new or existing systems, including those that may include existing determinations for applying substantially colorless marking material, but that can be subject to missing identification of pixel locations, which can result in lower quality output documents. For example, in some embodiments, memory  608  or storage  610  is configured to store non-transitory computer executable instructions such that when the executable instructions are executed by a computer or processor  604 , and cause a computer or processor to automatically perform a method (e.g., method  100 ) for processing image data for outputting documents. In embodiments of the present disclosure, the processor(s), for example, may be made in hardware, firmware, software, or various combinations thereof. The system  600  may be a computer system which includes a bus or other communication mechanism for communicating information, and one or more of its processing elements may be coupled with the bus for processing information. Also, the machine-readable instructions may be stored in various mechanisms for storing and/or transmitting information in a form that may be read by a machine (e.g., a computing device). For example, a machine-readable storage medium may comprise RAM or other dynamic storage devices (a floppy disk and disk drive, a writable optical disk and disk drive (CD-ROM), a hard disk and disk drive, flash memory, or the like), and may be distributed among separate memory components. Storage device  610  may include read only memory (ROM) or other static storage device coupled to the bus to store executable instructions for the processor or computer. Alternatively, another storage device, such as a magnetic storage disk or optical storage media, may also be coupled to the bus for storing information and instructions. Such devices are not meant to be limiting. In an embodiment, a machine-readable transmission media may include forms of propagated signals, including carrier waves, infrared signals, digital signals, and other media for transmitting information. While firmware, software, routines, or instructions may be described in the above disclosure in terms of specific exemplary aspects and embodiments performing certain actions, it will be apparent that such descriptions are merely for the sake of convenience and that such actions in fact result from computing devices, processing devices, processors, controllers, or other devices or machines executing the firmware, software, routines, or instructions. 
     In alternative embodiments, hard-wired circuitry may be used in place of or in combination with software instructions to implement the disclosure. Thus, embodiments of this disclosure are not limited to any specific combination of hardware circuitry and software. Any type of computer program product or medium may be used for providing instructions, storing data, message packets, or other machine readable information associated with the method  100 ,  200 , and/or  300 . The computer readable medium, instructions, or product should not be limiting. 
     In addition, it should be noted that the system/apparatus  600  may include a local display or control panel user interface (UI) that allows a customer to read input, instructions, and features for processing image data. The user interface may be used to alternatively set the system or to select to implement the method  100  of  FIG. 1 , previously described. The location and accessibility of the features on the display/control panel interface should not be limiting. For example, a user may scroll through a list of processing features by accessing them directly on the machine or on a computer. 
     The methods described herein can be used with any number of applications, including, but not limited to, office environments. For example, the application of substantially colorless marking material to text portions of bills may be beneficial, so that the vulnerability for amounts or addresses to be scraped or rubbed off is substantially reduced and/or prevented. Any number of industries can utilize the herein disclosed methods. 
     While the principles of the disclosure have been made clear in the illustrative embodiments set forth above, it will be apparent to those skilled in the art that various modifications may be made to the structure, arrangement, proportion, elements, materials, and components used in the practice of the disclosure. 
     While this disclosure has been described in connection with what is presently considered to be the most practical and preferred embodiments, it is to be understood that it is capable of further modifications and is not to be limited to the disclosed embodiments, and this disclosure is intended to cover any variations, uses, equivalent arrangements or adaptations of the inventive concepts following, in general, the principles of the disclosed embodiments and including such departures from the present disclosure as come within known or customary practice in the art to which the embodiments pertains, and as may be applied to the essential features hereinbefore set forth and followed in the spirit and scope of the appended claims. 
     It will be appreciated that various of the above-disclosed and other features and functions, or alternatives thereof, may be desirably combined into many other different systems/devices or applications. Various presently unforeseen or unanticipated alternatives, modifications, variations, or improvements therein may be subsequently made by those skilled in the art which are also intended to be encompassed by the following claims.