Hewlett-packard Development Company, L.P.

Hewlett-packard Company

Rochester Institute of Technology

Ranjit Bhaskar

Jay Stephen Gondek

Morgan Thomas Schramm

Wesley R Schalk

Kevin R Hudson

Mark Edward Shaw

Jesse Otto Sutherland

Eli S Saber

Jefferson Patrick Ward

Sohail A Dianat

Steven O Miller

Stuart Douglas Spencer

Sreenath Rao Vantaram

Je-Ho Lee

Erik A Anderson

Thomas Berge

Vladimir Misic

Angel Astorgano-Ballesteros

Praveen Boppana

Guru Prashanth Balasubramanian

Eric Robert Peskin

Jay S Gondak

Example color resources are generated. A first luminosity amount of a greyscale color in a greyscale color space is determined. The greyscale color corresponds with a transformation of a source color in a first color space converted to the greyscale color. The source color corresponding with a depletion color in a second color space, and the depletion color has a second luminosity amount. A target color in a color resource is generated via adjusting a black channel amount in the depletion color to match the second luminosity amount with the first luminosity amount. The target color to correspond with the source color in the color resource.

Color resources

An image file is prepared for printing. The image file is received. The image file includes a cell having pixels. A pixel of the pixels of the cell corresponds with a command to apply a print substance to a medium. For the pixel, the command to apply the print substance is selectively replaced with a command to not apply the print substance.

Selective reduction of print substance consumption

Target color table generated from source color tables. A first significance factor is assigned to a first node in a first source color table. The first node in the first source color table corresponds with a color input in a first color space and provides a first print substance formulation in a second color space. A second significance factor is assigned to a second node in a second source color table. The second node in the second source color table corresponds with the color input in the first color space and provides a second print substance formulation in the second color space. A third node in target color table is generated from the first and second nodes based on the first and second significance factors. The third node corresponds with the color input in the first color space and provides a third print substance formulation in the second color space.

Color table generation

An example color resource is generated. A source color from a first color space is converted to a corresponding greyscale color in a greyscale color space. The greyscale color includes a first luminosity amount. A black channel amount is adjusted to a depletion color from a second color space to form a target color in the second color space. The depletion color corresponds with a transformation of the source color into the second color space. The depletion color includes a second luminosity amount, and adjusting the black channel includes matching the second luminosity amount in the target color with the first luminosity amount.

In one example in accordance with the present disclosure, a printing system is described. The printing system includes a media sensor to detect a presence of media at a particular point within the printing system. A stepper motor moves media through the printing system. A controller 1) monitors, for at least one pass of the media, a number of steps of the stepper motor to pass the media between the media sensor and a print position, 2) stores the number of steps of the stepper motor in a memory device, and 3) adjusts operation of subsequent passes of the media based on stored number of steps. A memory device of the printing system stores the number of steps of the stepper motor, for at least one pass of the media.

Stepper motor-based print adjustments

A multi-resolution color image segmentation algorithm which takes advantage of gradient information in an adaptive and progressive framework is described. A gradient-based segmentation method is initiated with a dyadic wavelet decomposition scheme of an arbitrary input image, accompanied by a vector gradient calculation of its color converted counterpart. The resultant gradient map is used to automatically and adaptively generate thresholds for segregating regions of varying gradient densities, at different resolution levels of the input image pyramid. In combination with a confidence map and non-linear spatial filtering techniques, regions of high confidence are passed from one resolution level to another until the final segmentation at highest (original) resolution is achieved.

Methods for adaptive and progressive gradient-based multi-resolution color image segmentation and systems thereof

A method for segmenting an image includes computing a color gradient map based on an inputted image and selecting at least one initial seed of at least one pixel based on the color gradient map. The method further includes growing a region of pixels adjacent to the initial seed and merging adjacent regions of pixels using a measure of similarity.

Unsupervised color image segmentation by dynamic color gradient thresholding

Systems, devices, and methods performed by program instructions, are provided for color map selection. One method includes instructions which execute to generate a first color map from a set of colors. The instructions execute to generate a second color map from the set of colors and an additional color and to select a color value from between the first color map and the second color map dependent on a presence of the additional color.

Color map selection

A test page produced by ink pens for calibrating drop weights for at least a first and a second printheads, comprising: a page with an area for color swatches; a plurality of color swatches disposed in the area; and a predetermined substantially uniform color background disposed in said area between and around said plurality of color swatches. In a system embodiment of the present invention, a sensor may be used for sensing spectral data for each color swatch in a plurality of color swatches; and a component may be provided for comparing the sensed spectral data for each color swatch in a plurality of the color swatches to spectral data for the background color and selecting one of the plurality of color swatches which has spectral data which is closest to the background color for use in adjusting ink volume for at least one of the ink pens.

Color calibration chart

A method of compressing a set of image data organized into a matrix of pixels includes selecting a multi-pixel block portion of the data, then performing a mathematical function on the multi-pixel block portion to generate a first result. The multi-pixel block portion is divided into at least two segments, and a function is performed on each of the segments to generate a second result and a third result. Based on a comparison of the first, second, and third results, determining whether or not to compress the multi-pixel block portion. The function may be a deviation or mean measurement and serve to determine the noise level and image detail level to determine whether to compress or divide the block into sub blocks. Sub blocks may be recursively analyzed for compression or subdivision until all sub blocks are compressed or divided into single pixels.

Image data compression method

Optimally determined halftoning algorithms are applied to tone values by selecting among combinations of at least two algorithms that best address the tradeoff between output quality and rendering performance. Input tone values are scrutinized and matched with the algorithm combination that processes the associated tone values in a manner that increases performance (including data compressibility) without sacrificing output quality. The selection process is computationally simple and fast. Reliability is ensured because the combinations of halftoning algorithms are tabulated as a result of analysis of test samples of the printed output.

Tone dependent variable halftoning with adjustable algorithm selection

An automatic contrast enhancement method improves the quality of an image by increasing the dynamic range of the tone levels in an image without causing an undesirable hue shift. An overall stretch factor that stretches the dynamic range of all the colors is generated based on the standard deviation of the tone levels for the overall luminance of the image. A color weighting factor is used to individually control the amount that each color is stretched. The color weighting factor is based on the difference between the standard deviation of the tone levels for the overall luminance of the image and the standard deviation of the tone levels for each color. An anchor factor is used to preserve the mean tone level for each color while the tone levels far from the mean tone level are changed more dramatically than the tone levels close to the mean tone level, which minimizes hue shifts while maximizing contrast enhancement.

Growing community of inventors

Portland, OR, United States of America

Ranjit Bhaskar