Abstract: Image object adjustment is achieved without lookup tables or templates. Cross sections of image objects are modeled. Parameters of the modeled cross-section are adjusted in accord with a desired effect. For example, a width of the modeled cross section is change. The changed cross section model is sampled to determine a new value for a target pixel. For instance, vector windows are applied to a target pixel. If a candidate image object is included in the vector window, a cross section thereof is modeled as a rectangle. A parameter of the model, such as a width, is adjusted. Area sampling of the adjusted model can be used to determine a new value for the target pixel. Accuracy can be increased by blending information associated with a plurality of vector windows.

Abstract: The teachings provided herein disclose an image processing method for rendering a digital image possessing anti-aliased pixels by selecting a target pixel location within the digital image; observing a set of pixels within a pixel observation window superimposed on the digital image relative to the target pixel location; generating edge-state codes for a plurality of pairs of neighboring vectors of pixels within the pixel observation window; generating edge-identification codes from the plurality of edge-state codes using at least one look-up table; and, utilizing the edge-identification codes to select and apply to the digital image at the target pixel either anti-aliased rendering or conventional halftoning. The anti-aliasing may employ pixel signals that are high addressable and directionally biased to a particular orientation.

Abstract: Defects in an image forming system may give rise to scratched fiducials, missing fiducial regions, or other defects in an image that can run parallel to the process direction. The present disclosure provides for a fiducial compensation method and system for detecting defects thereby allowing spatial tone reproduction curves to be calculated and applied to a digital image in order to eliminate printed streaks due to a photoreceptor's non-uniformities.

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 method is provided for segmenting scanned image data in accordance with mixed raster content processing, further including windowing for purposes of extracting particularly classifiable objects, i.e., text, graphics or pictures. Application of predetermined parameter sets selected for more precise identification of the extracted objects are applied to the data for object extraction, object selection, color uniformity, and clustering for coloring similarity. A page background detection feature uses dual thresholding for segregating text (darker) areas from non-text (brighter) areas. Two histograms are created for the respective areas. Thresholds are generated from the two histograms and applied to the respective areas separately.

Abstract: This invention relates to an imaging device that extends the processing of resources to data having a greater bit-depth. A signal having data at the first bit-depth is received, and at least a portion of the data at the first bit-depth is converted into an estimated value that is at the second bit-depth. A residual that indicates a difference between the data and the estimated value is determined. The estimated value is processed through the resource to form processed data that is at the second bit-depth. The data is then substantially recovered at the first bit-depth from the processed data that is at the second bit-depth and based on the residual.

Abstract: A streak detection method and system in a fixed imaging array digital scanning system obtains image data from each of the plurality of rows in the at least one full color spectrum channel set of rows of positionally discrete sensors and integrates this data to produce an estimate of image data recorded by at least one clear channel row of positionally discrete sensors. A clear channel error signal is generated by the comparison to alert the operator to the presence of non-image data. The clear channel error signal may be refined to through a low pass column filtering process in order to filter out potentially erroneous clear channel error resulting from thermal, mechanical or other noise sources unrelated to image scanning. Stationary obstructions in the field of view of the imaging array, or defects in one or more sensors in the imaging array, are detected through this comparison which would otherwise appear repeatedly reproduced as streaks or lines in the reproduced output image.

Abstract: Apparatus are provided, including a macrouniformity compensation mechanism to modify data exchanges between device-independent image data and a one-dimensional imaging device, to compensate for a lack of macrouniformity caused by the one-dimensional imaging device. The macrouniformity compensation mechanism includes an input-output value converter to convert an input intensity value for a given pixel to a corresponding output intensity value. The output intensity value is determined as a function of the position of the given pixel in the cross-process direction of the image and the level of the input intensity value. The input-output value converter includes a number of stored conversion parameter sets corresponding to respective different positions in the cross-process direction of the pixel data. The number of stored conversion parameter sets is a fraction of the total number of pixel positions in the cross-process direction of the pixel data.

Abstract: The teachings provided herein disclose a method for the identification of edge pixels within a digital image. The method operates by generating edge-state codes for a plurality of pairs of neighboring vectors of pixels within a given observation window, and generating an edge-identification code from the plurality of edge-state codes using a look-up table. The edge identification provides information that can be used for subsequent treatments such as rendering anti-aliased pixels, selecting preferred halftoning and tone reproduction for edge pixels, corner sharpening, and object recognition and segmentation.

Abstract: The teachings provided herein disclose an image processing method for rendering a digital image possessing anti-aliased pixels by selecting a target pixel location within the digital image; observing a set of pixels within a pixel observation window superimposed on the digital image relative to the target pixel location; generating edge-state codes for a plurality of pairs of neighboring vectors of pixels within the pixel observation window; generating edge-identification codes from the plurality of edge-state codes using at least one look-up table; and, utilizing the edge-identification codes to select and apply to the digital image at the target pixel either anti-aliased rendering or conventional halftoning. The anti-aliasing may employ pixel signals that are high addressable and directionally biased to a particular orientation.

Abstract: The teachings provided herein disclose a method for producing digital image objects with enhanced halftone edges. The method operates by selecting a target pixel location within the digital image; observing a set of pixels within a pixel observation window superimposed on the digital image relative to the target pixel location; generating edge-state codes for a plurality of pairs of neighboring vectors of pixels within the pixel observation window; generating edge-identification codes from the plurality of edge-state codes using at least one look-up table; and, utilizing the edge-identification code to select and apply to the digital image at the target pixel either a first halftone screen having a first fundamental frequency and a first angle or a second halftone screen having a second fundamental frequency and a second angle, wherein the second frequency and second angle are harmonically matched to the first frequency and first angle.

Abstract: The teachings provided herein disclose a method for corner sharpening in the display of a bitmapped digital image. The method includes the steps of selecting a target pixel location within the digital image; observing a set of pixels within a pixel observation window superimposed on the digital image relative to the target pixel location; generating edge-state codes for a plurality of pairs of neighboring vectors of pixels within the pixel observation window; generating corner-identification codes from the plurality of edge-state codes using at least one look-up table so as to thereby identify corner pixels; and, assigning a pixel value in an output image plane in a location corresponding to the target pixel in the input image, such that assigned value extends a corner where indicated by a corner identification code, thereby producing a sharpening effect. The method may be used for improving the print quality of line-art corners and other fine details as found in both font and image data.

Abstract: A method is provided for segmenting scanned image data in accordance with mixed raster content processing, further including windowing for purposes of extracting particularly classifiable objects, i.e., text, graphics or pictures. Application of predetermined parameter sets selected for more precise identification of the extracted objects are applied to the data for object extraction, object selection, color uniformity, and clustering for coloring similarity. A page background detection feature uses dual thresholding for segregating text (darker) areas from non-text (brighter) areas. Two histograms are created for the respective areas. Thresholds are generated from the two histograms and applied to the respective areas separately.

Abstract: Image object adjustment is achieved without lookup tables or templates. Cross sections of image objects are modeled. Parameters of the modeled cross-section are adjusted in accord with a desired effect. For example, a width of the modeled cross section is change. The changed cross section model is sampled to determine a new value for a target pixel. For instance, vector windows are applied to a target pixel. If a candidate image object is included in the vector window, a cross section thereof is modeled as a rectangle. A parameter of the model, such as a width, is adjusted. Area sampling of the adjusted model can be used to determine a new value for the target pixel. Accuracy can be increased by blending information associated with a plurality of vector windows.

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 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: 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: System and methods provide a message, generated based on a message authentication code (MAC), embedded in a look-up table associated with an image. The embedding of the message does not affect the image. The message may be used to authenticate the image.

Abstract: In a machine-fed scanner, orientation angles of edges of an image bearing substrate are obtained and used to calculate image shear and/or skew. A running weighted average of the image skew may be kept in a memory. When a skew value is obtained for a given image, it may be determined whether the skew value is within a predetermined range. If the skew value is within the predetermined range, the skew value is used to determine an image revision to compensate for the skew, and the skew value is incorporated into the running weighted average skew. If the skew value is not within the predetermined range, it is discarded and the running weighted average skew is used to determine an appropriate image skew revision. The running weighted average of the shear may also be kept in a memory. A shear value is obtained for each image, and incorporated into the running weighted average shear. Shear revision is performed based on the running weighted average shear.

Abstract: An annular window-shaped structuring element is provided for image processing to remove speckles from a scanned image. The window-shaped structuring element is composed of two differently sized squares sharing the same geometric center-point. The pixel to be analyzed with the structuring element is at the center-point. The structuring element is used in a method to remove speckles from binary, grayscale, and/or color images by first eroding the image, detecting speckles relative to other pixels in the image, and removing declared speckles. The method may additionally include a halftoning module to protect halftone images.