Abstract: Various embodiments for methods and systems for processing a document are disclosed. A font size associated with each of one or more text regions included in the document is determined. A first resolution of each of the one or more text regions is modified based on respective font size associated with each of the one or more text regions to generate a multi-resolution document.

Abstract: A method and system generates a reconstructed gray scale image of pixels from a binary image of pixels by reverse propagating an error, in a diffused manner, to the pixels of the binary image to create pixels representing a reconstructed gray scale image. The reverse propagation of the error determines if a current pixel has a first predetermined value; sets an error value to a first error value if the current pixel has the first predetermined value; sets the error value to a second error value if the current pixel does not have the first predetermined value; and propagates a diffused error value to a pixel neighboring the current pixel to create an error diffused pixel, the diffused error value being a product of the set error value and a weighting coefficient associated with the pixel neighboring the current pixel. A Gaussian filter may be utilized to filter the pixels representing a gray scale image to create a filtered reconstructed gray scale image of pixels.

Abstract: A method and system for segmenting text from non-text portions of a digital image using the size, solidity, and run length characteristics of connected components within the image data. For a connected component comprising a rectangular group of pixels enclosing a set of connected pixels having the same binary state, the size characteristic may be based on a ratio of height to width of the connected component and the total number of pixels within the connected component, the solidity characteristic may be based on a ratio of pixels within a convex hull of the set of connected pixel to a total number of pixels within the connected component, and the run length characteristic may be based on a number of transitions within the connected component.

Abstract: Methods and systems receive an input image into a computerized device, create different binary images by applying different threshold measures to the input image using the computerized device, and identify components of a first binary image of the binary images using the computerized device. Such methods and systems also compare pixels of each of the components of the first binary image with corresponding pixels of a second binary image of the binary images to identify pixel differences using the computerized device. This allows these methods and systems to identify halftone areas within the input image based on the pixel differences exceeding a limit using the computerized device.

Abstract: In response to N-up instructions methods and systems analyze the sizes of printable items within full-size pages to be printed, and determine the minimum size to which each of the full-size pages can be reduced to keep all the printable items above a minimum print item or font size. Because different pages of the print/copy job can have differently sized printable items, at least two of the full-size pages can have a different minimum size to which they can be reduced. Such methods and systems automatically reduce the sizes of the full-size pages (as limited by each potentially different minimum size of each different full-size page) to produce reduced-size pages that will be combined on output pages. Again, because each different full-size page can have a different minimum size, at least two of the full-size pages can be reduced by different reduction amounts during the reduction process.

Abstract: Methods and systems divide an image into image blocks, determine a number of high-variation blocks within valid image blocks, determine a page variance measure by dividing the number of high-variation blocks by the total number of valid image blocks, and classify the image as comprising a halftone and/or text image if the page variance measure exceeds a halftone threshold. Such methods and systems classify the image as being a continuous tone image if the page variance measure does not exceed the halftone threshold and a text index is below a text index threshold, and classify the image as being a continuous tone and text image if the page variance measure does not exceed the halftone threshold and the text index is not below the text index threshold. Further, such methods and systems select an image processing mode based on such image classifications.

Abstract: Methods and systems receive an input image into a computerized device, create different binary images by applying different threshold measures to the input image using the computerized device, and identify components of a first binary image of the binary images using the computerized device. Such methods and systems also compare pixels of each of the components of the first binary image with corresponding pixels of a second binary image of the binary images to identify pixel differences using the computerized device. This allows these methods and systems to identify halftone areas within the input image based on the pixel differences exceeding a limit using the computerized device.

Abstract: Methods and systems divide an image into image blocks, determine a number of high-variation blocks within valid image blocks, determine a page variance measure by dividing the number of high-variation blocks by the total number of valid image blocks, and classify the image as comprising a halftone and/or text image if the page variance measure exceeds a halftone threshold. Such methods and systems classify the image as being a continuous tone image if the page variance measure does not exceed the halftone threshold and a text index is below a text index threshold, and classify the image as being a continuous tone and text image if the page variance measure does not exceed the halftone threshold and the text index is not below the text index threshold. Further, such methods and systems select an image processing mode based on such image classifications.

Abstract: A processor-implemented method for processing image data of a document using an apparatus or medium. The processor determines a billable color pixel count in an image by determining a first count of color pixels in the image data in device independent space (e.g., fuzzy and true color counts using a neutral page determination) and a second count of color pixels in device dependent space (e.g., binary CMYK based count). The first and second counts are transformed and a minimum of the transformation is used as the billable count. Based on the disclosed implementation, billing accuracy for outputting color documents is improved and flexibility in tier-based billing is preserved.

Abstract: Disclosed is a processor-implemented method for processing image data of a document using an apparatus. The processor determines pixel classifications and counts for each classification, classifies the image, selects a billing tier for which to bill the image, determines counts of pixels for marking to output the image (e.g., in device dependent space), and then can adjust from the selected billing tier to a different billing tier based on the image classification (e.g., and/or using determined counts of pixels for each classification and determined counts of pixels for marking). Counts of pixels can be adjusted using an offset, or calculated using a combination of the determined counts (e.g., combining counts from both independent and dependent spaces). By adjusting the tier at which to bill data, more accurate billing can be implemented for documents with contone or grayscale image data, for example, with greater customer satisfaction.

Abstract: A method and system generates a reconstructed gray scale image of pixels from a binary image of pixels by reverse propagating an error, in a diffused manner, to the pixels of the binary image to create pixels representing a reconstructed gray scale image. The reverse propagation of the error determines if a current pixel has a first predetermined value; sets an error value to a first error value if the current pixel has the first predetermined value; sets the error value to a second error value if the current pixel does not have the first predetermined value; and propagates a diffused error value to a pixel neighboring the current pixel to create an error diffused pixel, the diffused error value being a product of the set error value and a weighting coefficient associated with the pixel neighboring the current pixel. A Gaussian filter may be utilized to filter the pixels representing a gray scale image to create a filtered reconstructed gray scale image of pixels.

Abstract: In response to N-up instructions methods and systems analyze the sizes of printable items within full-size pages to be printed, and determine the minimum size to which each of the full-size pages can be reduced to keep all the printable items above a minimum print item or font size. Because different pages of the print/copy job can have differently sized printable items, at least two of the full-size pages can have a different minimum size to which they can be reduced. Such methods and systems automatically reduce the sizes of the full-size pages (as limited by each potentially different minimum size of each different full-size page) to produce reduced-size pages that will be combined on output pages. Again, because each different full-size page can have a different minimum size, at least two of the full-size pages can be reduced by different reduction amounts during the reduction process.

Abstract: A processor-implemented method for processing image data of a document using an apparatus or medium. The processor determines a billable color pixel count in an image by determining a first count of color pixels in the image data in device independent space (e.g., fuzzy and true color counts using a neutral page determination) and a second count of color pixels in device dependent space (e.g., binary CMYK based count). The first and second counts are transformed and a minimum of the transformation is used as the billable count. Based on the disclosed implementation, billing accuracy for outputting color documents is improved and flexibility in tier-based billing is preserved.

Abstract: Disclosed is a processor-implemented method for processing image data representing a document using an image processing apparatus. The processor receives image data, determines the classifications and counts of pixels in the image data (e.g., in device independent space that are degrees of neutral or non-neutral), classifies the image data into a category based on the determination of classifications and counts of pixels, and determines a billing structure for the image data based on the classification of image data. The classification can be performed on the image data prior to conversion into device dependent space. For example, by counting true color, neutral, non-neutral, and fuzzy color pixels and comparing them to thresholds, the image data can be classified as neutral or very colorful. By classifying images earlier in the image path, errors in billing are reduced.

Abstract: Disclosed is a processor-implemented method for processing image data of a document using an apparatus. The processor determines pixel classifications and counts for each classification, classifies the image, selects a billing tier for which to bill the image, determines counts of pixels for marking to output the image (e.g., in device dependent space), and then can adjust from the selected billing tier to a different billing tier based on the image classification (e.g., and/or using determined counts of pixels for each classification and determined counts of pixels for marking). Counts of pixels can be adjusted using an offset, or calculated using a combination of the determined counts (e.g., combining counts from both independent and dependent spaces). By adjusting the tier at which to bill data, more accurate billing can be implemented for documents with contone or grayscale image data, for example, with greater customer satisfaction.

Abstract: Disclosed is a processor-implemented method for processing image data representing a document using an image processing apparatus. The processor receives image data, determines the classifications and counts of pixels in the image data (e.g., in device independent space that are degrees of neutral or non-neutral), classifies the image data into a category based on the determination of classifications and counts of pixels, and determines a billing structure for the image data based on the classification of image data. The classification can be performed on the image data prior to conversion into device dependent space. For example, by counting true color, neutral, non-neutral, and fuzzy color pixels and comparing them to thresholds, the image data can be classified as neutral or very colorful. By classifying images earlier in the image path, errors in billing are reduced.

Abstract: Disclosed is a processor-implemented method for processing image data comprising a plurality of pixels and system for performing the method. The method includes the following acts: determining at least one type of data represented by the plurality of pixels, determining, for each type of data, a number of pixels from the image data representing that type of data in the image data, and determining a compression scheme for compressing the image data based on a relative or absolute amount of each type of data in accordance with a predetermined scheme. The type of data may be determined by received input (e.g., user selected type and compression quality) or by analyzing its pixels and comparing it to thresholds. Basing the compression technique on the data type allows for better selection of a compression technique (e.g., MRC or JPEG), and thus greater image quality, compression ratios, and file size.

Abstract: A method for performing binary image reduction on binary image data includes receiving binary input image data; determining a conversion factor to scale (i) an input resolution to an output resolution and/or (ii) an input size to an output size; applying the conversion factor to the input image data to obtain intermediate data, where each intermediate data corresponds to at least one input pixel and at least a portion of another input pixel; obtaining a binary output image data comprising a plurality of output pixels by thresholding the corresponding intermediate data; determining an error value for each output pixel, the error value is a non-integer value obtained as a result of thresholding the intermediate data corresponding to the output pixel; and propagating the obtained error value to an adjacent output pixel in a scanline, where the output image data is scaled to the output resolution and/or the output size.

Abstract: Disclosed herein is a system and method for diagnosing a failure condition of an image processing apparatus. When a failure condition is detected in an image path during output of a document, a fault code is issued. The image processing apparatus is then capable of performing an internal diagnosis to generate a diagnostic report, and send the diagnostic report and fault code to an operator at a remote location. The system and method allows one to diagnose a problem or failure condition more quickly and efficiently, thereby cutting down on service time and costs.

Abstract: A method and apparatus for configuring an image path of an image processing apparatus is herein described. The image processing apparatus includes at least an input terminal or scanner for inputting or scanning document into image data and an output terminal or printer for printing documents. The method includes selecting one of a plurality of output modes using a selection device associated with the image processing apparatus. Based on the selected output mode, an image path among a plurality of image processing elements of the apparatus is selected among a plurality of image paths. Each image path corresponds to one of the plurality of output modes. After a document is scanned with the scanner into image data, the image data is processed with the processing elements in the selected image path, and output or printed based on the processed image data.