Abstract: Disclosed is a method and system for processing image data, which may be generated by a scanning subsystem, and the segmentation and treatment of leaky windows or segments within the image. In addition to the identification of window regions or segments having leaky boundaries, the method and system include the subsequent control of enhancement and other image processing techniques applied to such images so as to reduce or eliminate artifacts that result from the processing of leaky window regions.

Abstract: A device (200) for manufacturing a color printing includes a printhead (10), a device (300) for additional printing of the color printing, and a printhead motion and jetting control (100). The device (300) also provided herein includes a printhead identification unit (80) and the host processor (90). The printhead identification unit is configured for identifying type of the N jets, calculating the numbers of the defective jets, and then outputting measurement information of the N jets and the defective jets. The host processor is configured for receiving the measurement information from the printhead identification unit and outputting movement instructions of the printhead with a starting position of the printhead in the first printing process.

Abstract: Methods and apparatus for segmenting image data into windows and rendering a best-estimate outline delineating document windows may include adjusting a background white threshold differently than adjusting a white threshold normally used to classify pixels as white for video processing purposes. Such an independently arrived at threshold may be more suitable for the different task of differentiating between document background and document content.

Abstract: A system and method remove at least one color from a color image in a chrominance-luminance color space. The processing method includes generating screen values for machine independent color space image pixels, comparing the screen values for the pixels with pixel values for one component of the machine independent color space, and generating a dropout pixel for each pixel having a screen value that is less than the pixel value for the one component of the machine independent color space. The screen value for a pixel may be compared to the pixel value for the luminance component to determine whether to generate a dropout pixel or not.

Abstract: A method for dynamic range adjustment of image data of a captured image by determining a white point of an image. The method also involves determining a black point of the image, classifying pixels of the image, and determining an offset value for a pixel of the image based on the determined black point of the image and the determined classification of the pixel. Dynamic range adjustment of the image data is performed using the determined offset value for the pixels of the image and the determined white point of the image.

Abstract: A device (200) for manufacturing a color printing includes a printhead (10), a device (300) for additional printing of the color printing, and a printhead motion and jetting control (100). The device (300) also provided herein includes a printhead identification unit (80) and the host processor (90). The printhead identification unit is configured for identifying type of the N jets, calculating the numbers of the defective jets, and then outputting measurement information of the N jets and the defective jets. The host processor is configured for receiving the measurement information from the printhead identification unit and outputting movement instructions of the printhead with a starting position of the printhead in the first printing process.

Abstract: A method and apparatus are provided for the processing of an image, such as a document. The invention determines the location of differing content types within the document allowing specialized processing of various content types. The invention performs the identification of pixels having similar content characteristics into windows during the first scanning pass of the document by the use of an identifier equivalence table to update selected memory locations to a base identifier during processing. A second pass processing is available to enhance or alter the image by the use of the information gathered during first pass processing. The present invention benefits from a very low memory requirement while being able to determine windows extending the length or width of the image.

Abstract: A method to detect frequency and angle of a binary halftone pattern. The method employs an exclusive-or operation which is applied locally to a region of a binary bit map and its spatially shifted version. The resulting bits from the exclusive-or operation are summed over the region. The exclusive-or operation is repeated for a range of shift values. In a halftone region, the shift at which the minimum sum occurs reflects the angle and the frequency of the halftone.

Abstract: Methods and apparatus may include assigning a subtype, from a sub-class of image types, to a pixel, the subtype indicating membership in a window and also indicating a more specialized sub-class of image types. Membership in the sub-class may specify downstream processing specific to the subtype and compatible with the downstream processing of other subtypes within the sub-class. Such methods and apparatus may allow individual pixels within a window to receive specialized downstream processing according to their subtype while preventing objectionable artifacts. Such artifacts may result from classifying neighboring pixels as image types calling for mutually incompatible downstream processing.

Abstract: Methods and apparatus for segmenting image data into one or more windows may collect statistics on white regions, otherwise called enclosed white windows. Such enclosed white windows may be merged with one of a surrounding nonwhite window and a background based upon the enclosed white window's size, edge characteristics, cumulative statistics and/or at least one control parameter. Such merging may be accomplished at a time subsequent to enclosing the white region or dynamically while the window is being assembled scanline-by-scanline.

Abstract: Methods and apparatus for segmenting image data into windows and rendering a best-estimate outline delineating document windows may include adjusting a background white threshold differently than adjusting a white threshold normally used to classify pixels as white for video processing purposes. Such an independently arrived at threshold may be more suitable for the different task of differentiating between document background and document content.

Abstract: A system and method remove at least one color from a color image in a chrominance-luminance color space. The processing method includes generating screen values for machine independent color space image pixels, comparing the screen values for the pixels with pixel values for one component of the machine independent color space, and generating a dropout pixel for each pixel having a screen value that is less than the pixel value for the one component of the machine independent color space. The screen value for a pixel may be compared to the pixel value for the luminance component to determine whether to generate a dropout pixel or not.

Abstract: Disclosed is a method and system for processing image data, which may be generated by a scanning subsystem, and the segmentation and treatment of leaky windows or segments within the image. In addition to the identification of window regions or segments having leaky boundaries, the method and system include the subsequent control of enhancement and other image processing techniques applied to such images so as to reduce or eliminate artifacts that result from the processing of leaky window regions.

Abstract: A continuously variable screening tool is used to generate a unique texture pattern for every color in a multicolor image. The continuously variable screening tool allows a single colorant version of the image to be generated with less information loss than typically suffered in the multicolor to single color transformation process. The continuously variable screening tool is generated by blending patterns from a set of reference screens. The reference screens are associated with selected reference colors in, for example, a machine independent color space. A calculated screen is generated through a weighted blend of reference screens located near the arbitrary color in the machine independent color space. Typically, the weights depend on the distance the arbitrary color is from each of the reference colors. The screens consist of arrays of threshold values. Each threshold value is associated with a dot position and an image pixel.

Abstract: A method for dynamic range adjustment of image data of a captured image by determining a white point of an image. The method also involves determining a black point of the image, classifying pixels of the image, and determining an offset value for a pixel of the image based on the determined black point of the image and the determined classification of the pixel. Dynamic range adjustment of the image data is performed using the determined offset value for the pixels of the image and the determined white point of the image.

Abstract: A pixel classification method for classifying pixels of an image by determining a background intensity level of an image which is based on substantially all of the pixels of the image. The method also involves classifying the pixels of the image and checking the classification of the pixel based on the determined background intensity level of the image.

Abstract: A method and system for image processing, in conjunction with classification of images between natural pictures and synthetic graphics, using SGLD texture (e.g., variance, bias, skewness, and fitness), color discreteness (e.g., R_L, R_U, and R_V normalized histograms), or edge features (e.g., pixels per detected edge, horizontal edges, and vertical edges) is provided. In another embodiment, a picture/graphics classifier using combinations of SGLD texture, color discreteness, and edge features is provided. In still another embodiment, a “soft” image classifier using combinations of two (2) or more SGLD texture, color discreteness, and edge features is provided. The “soft” classifier uses image features to classify areas of an input image in picture, graphics, or fuzzy classes.

Abstract: A method to detect frequency and angle of a binary halftone pattern. The method employs an exclusive-or operation which is applied locally to a region of a binary bit map and its spatially shifted version. The resulting bits from the exclusive-or operation are summed over the region. The exclusive-or operation is repeated for a range of shift values. In a halftone region, the shift at which the minimum sum occurs reflects the angle and the frequency of the halftone.

Abstract: A method and apparatus are provided for determining a weighted average measured reflectance parameter Rm for pixels in an image for use in integrated cavity effect correction of the image. For each pixel of interest Pi,j in the image, an approximate spatial dependent average Ai,j, Bi,j of video values in a region of W pixels by H scan lines surrounding the pixel of interest Pi,j is computed by convolving video values Vi,j of the image in the region with a uniform filter. For each pixel of interest Pi,j a result of the convolving step is used as the reflectance parameter Rm. The apparatus includes a video buffer for storing the pixels of the original scanned image, and first and second stage average buffers for storing the computed approximate spatial dependent averages Ai,j, Bi,j. First and second stage processing circuits respectively generate the first and second stage average values Ai,j, Bi,j by convolving the video values of the image in a preselected region with a uniform filter.

Abstract: A system and method classify a pixel of image data as one of a plurality of image types. A first image characteristic value for the pixel, a second image characteristic value for the pixel, a third image characteristic value for the pixel, and a fourth image characteristic for the pixel is determined. Some of these determinations may be resolution dependent. The values from these determination are utilized in assigning an image type classification to the pixel. Moreover, if at least one of the image characteristic values is greater than a predetermined threshold value the pixel is classified as a halftone peak value.