Xerox Corporation

Michael Branciforte

Robert P Loce

Beilei Xu

Reiner Eschbach

Stuart Alan Schweid

Yeqing Zhang

Son H Nguyen

Raja Bala

Leon C Williams

Ying-wei Lin

Ann Marie Cecchi

Zhigang Fan

R Victor Klassen

Robert Michael Lofthus

Grace T Brewington

Michael John Martin

Stephen C Morgana

Daniel R Maurer

Edward Neil Chapman

Michael E Farrell

David C Robinson

Douglas N Curry

Fritz F Ebner

William A Fuss

Vishal Monga

David E Rumph

Saurabh Prabhat

Roger Lee Triplett

Louis D Mailloux

Raymond J Clark

Thomas Robson

Farzin Blurfrushan

Russell B Rauch

Girmay K Girmay

Hung M Pham

Elizabeth Dubiel Wayman

Rosario A Bracco

James O Mitchel

Farhad D Rostamian

Abraham E Claproth

Cathleen J Raker

Daniel D Truong

Holly Elizabeth Turner

Sue K Lam

Robert R Thompson, Jr

Cheryl A Pence

Shahriar Vazan

Hoan N Nguyen

James F Oathout

Robert Paul Loce

Anne Marie Cecchi

To print a certified document, a user may select or a system may receive a selection of a document to be certified. The system identifies a security template to be used based on the document and/or capabilities of the print device on which the document will be printed. The system may display the document with a non-secure overlay of the selected security template, add a unique security element to the document according to the template, and cause the document to be printed at the selected print device with the added security element without permitting the added security element to be fully displayed or printed on any other device.

System for creating certified document copies

Systems and methods are described that facilitate identifying objects in a document (e.g., a PDF document) for automatic image enhancement (AIE). A PDF document is 'chunked' or segmented into chunks, and boundaries between chunks are identified as real or imaginary. Chunks sharing imaginary boundaries are combined, while real boundaries are retained, to generate 'de-chunked' objects. These objects are then classified, and an AIE application is executed on objects meeting pre-specified classification criteria. In this manner, objects of r which AIE is not desired are not subjected to the AIE application, thereby saving time and processing resources associated with enhancing the document.

PDF de-chunking and object classification

What is disclosed is a novel system and method for performing spatial gamut mapping on a received input color image having a plurality of pixels. A standard gamut-mapping algorithm is applied to the input color image to produce a gamut-mapped color image. A difference is computed between a selected channel of the input color image and the gamut-mapped image to produce a difference image. A local measure of complexity is derived for a given pixel in the difference image. One or more parameter values of a spatial bilateral filter are obtained from a lookup table based on the computed local measure of complexity. The spatial bilateral filter is applied, using the obtained parameter values, to the current pixel of the difference image to produce a modified pixel in a modified difference image. Thereafter, a modified gamut-mapped color image is obtained from the modified difference image and the gamut-mapped color image.

Adaptive spatial gamut mapping via dynamic thresholding

A method and system convert an original digital image being represented by a first color space to a digital image being represented by a second color space by transforming the original image data represented by a first color space to second image data being represented by a second color space, the transformation causing the colors of the transformed image data to be substantially encodable in the second color space. The second image data represented by the second color space is transformed to third image data represented by the first color space, the transformation causing the colors of the transformed image data to be substantially encodable in the first color space. Distortions in the third image data represented by the first color space are corrected to form corrected image data represented by the first color space, and the corrected image data represented by the first color space is transformed to fourth image data represented by the second color space.

System and method for color space conversion with reduced artifacts

An image characterized by an original image gamut is received in an imaging device characterized by a device gamut. The original image gamut is enhanced to a first set of modified color values that occupy a greater fraction of the device gamut than the original image gamut. The modified color values of each pixel are mapped to new color values within the device gamut.

Color image gamut enhancement preserving spatial variation

The present application is a method of 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. The method solves the problem of ragged edges on halftone tints as an automated, operation, with a computing architecture that is readily adapted to a wide variety of tinted edge conditions, and which can be readily adapted to real-time applications.

Tinted edge enhancement using look-up table edge pixel identification

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.

Corner sharpening using look-up table edge pixel identification

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.

Edge pixel identification

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.

Anti-aliased tagging using look-up table edge pixel identification

Error is distributed to pixels neighboring a pixel of interest based on a ranking of the neighboring pixels. The ranking is based on pixel values of the neighboring pixels. Optionally a spatial weighting is applied to the pixel values before ranking, to provide a preference for pixels closest to the pixel of interest or to a particular portion of a related halftone screen. Rank order based error diffusion provides compact halftone dots without patterning artifacts. An image processing system operative to perform rank order error diffusion includes a pixel ranker and an error diffuser. In a xerographic environment the image processing system includes a xerographic printer.

Rank-order error diffusion image processing

A method for rendering a raster output level determines an image position of a pixel of interest (POI) within an image. An intended raster output level, which corresponds to the POI, is received into a processing device. A final raster input level is determined as a function of the image position and the intended raster output level. The final input level and the image position are transmitted to an output device. An actual raster output level is rendered, via the output device, at a position on an output medium corresponding to the image position. The actual raster output level substantially matches the intended raster output level.

Macro uniformity correction for x-y separable non-uniform

Macro uniformity correction for x-y separable non-uniformity

A method for processing digital images to be displayed, stored, or printed, to eliminate blooming and other artifacts. The system utilizes morphological processes to isolate and modify image structures susceptible to marking process artifacts and then combines the modified image structures with the input image to produce a printable image that may be rendered on a given printer.

Logic-based image processing method

A method of reproducing a document including halftoned regions therein scans the document to generate scanned image data comprising a digitized representation of said document. The scanned image data that corresponds to the halftoned regions is then rendered using a compact rendering process that includes positioning an observation window about a target pixel and a neighboring pixel; selecting a fill-order based upon a result of the analyzing step; and generating a high addressability pixel as a function of the selected fill-order.

Compact-dot reproduction of scanned halftone screens

A compact rendering processor for processing image data including a multi-bit halftone region generates high addressability pixels. The compact rendering processor includes a tagging sub-processor operating on the image data to identify a target pixel and a neighboring pixel to determine a fill-order. The compact rendering processor also includes a rendering sub-processor that converts the target pixel into a high addressability pixel based upon the fill-order. Optionally, a diffusion sub-processor can be included to diffuse an error resulting from the conversion of the target pixel into a high addressability pixel to other pixels within the image data.

Compact high addressability rendering

Growing community of inventors

Rochester, NY, United States of America

Michael Branciforte