Abstract: Tools disclosed herein comprise progressive, paint stroke based region recognition and selection tools. Using these tools, a user may partially paint a region of interest directly on an image (by using a paint brush or other similar tool). Unlike conventional selection tools, a user is not required to paint the entire region pixel-by-pixel. Rather the desired region is automatically and intelligently recognized based on the partial selection. This is accomplished via a progressive selection algorithm. In addition, these tools provide the ability to quickly execute such region selections on multi-megapixel images.

Abstract: A method normalizes a feature of an object in an image. The feature of the object is extracted from a 2D or 3D image. The feature is displaceable within a displacement zone in the object, and wherein the feature has a location within the displacement zone. An associated description of the feature is determined. Then, the feature is displaced to a best location in the displacement zone to produce a normalized feature.

Abstract: A method and system for processing image data provides associated background metadata in a searchable format and reduces file size. MRC techniques are used to process input image data. It is known that the image data may be segmented to generate a background layer representing background attributes of the input image data. A background color value of the background layer is detected, and background metadata representing the color value is generated. The background metadata is associated with the image data (e.g., as a separate file, in the image header, etc.), thereby making the background metadata searchable and reducing the file size of the image data to be stored.

Abstract: An image-processing device includes: a memory that stores a red range occurring within a color space; an acquisition unit that acquires image data representing a document image that includes characters; and a production unit that produces image data representing an overall image that includes: the document image represented by the image data that is acquired by the acquisition unit, a differentiation image that is positioned within the document image and that allows the user to differentiate an image of red characters residing in the range from an image formed of colors other than red, and an information image representing information for acquiring the document image in a state in which the differentiation image is not positioned.

Abstract: Embodiments include a method of image processing including decomposing a reflectance spectrum for a test surface into a linear combination of reflectance spectra of a set of test targets. The coefficient vector calculated in this decomposition is used to predict a response of an imaging sensor to the test surface. A plurality of such predicted responses may be used for various applications involving color detection and/or classification, including human skin tone detection.

Abstract: Methods and systems for automatically generating a mask delineating a region of interest (ROI) within an image containing skin are disclosed. The image may be of an anatomical area containing skin, such as the face, neck, chest, shoulders, arms or hands, among others, or may be of portions of such areas, such as the cheek, forehead, or nose, among others. The mask that is generated is based on the locations of anatomical features or landmarks in the image, such as the eyes, nose, eyebrows and lips, which can vary from subject to subject and image to image. As such, masks can be adapted to individual subjects and to different images of the same subjects, while delineating anatomically standardized ROIs, thereby facilitating standardized, reproducible skin analysis over multiple subjects and/or over multiple images of each subject.

Abstract: The invention relates to a method for image processing. First, establish the initial image background information. And retrieve the instant image information. Then calculate the initial image background information and color intensity information of the instant image. Furthermore, adjust the instant image information. Then calculate the moving-object information. Finally, track the moving-object information. It can improve the accuracy rate of detection without the influence of erected height.

Abstract: An image processing apparatus is provided, the image processing apparatus including: a limited color conversion processing section that extracts plural pieces of color information constructing image information and converts the plural pieces of color information into color information representing specific colors to which each of the plural pieces of color information belongs; a by-color separation processing section that separates the image information containing the converted color information for each of the specific colors; a compression determination section that determines a compression system for each color as to each of pieces of image information which are separated by the by-color separation processing section for each of the specific colors; a compression processing section that compresses said each of pieces of image information according to the determined compression system for each color; and a layered structure forming processing section that collectively outputs said each of pieces of image in

Abstract: An imaging device is configured to include a dividing unit which divides a generated image into blocks, a white balance evaluation value acquiring unit which acquires color information and a white balance evaluation value of each block, a classifying unit which combines the blocks into areas based on the color information, a correction coefficient calculating unit which calculates a white balance correction coefficient for each of the areas, a white balance setting unit which sets the calculated white balance correction coefficient for each of the areas, and a green area determining unit which determines whether or not each of the blocks is a green area based on the color information. The white balance setting unit sets a different white balance correction coefficient for a block determined as a green area from the one set for the area including the block in question.

Abstract: The disclosure is directed to techniques for region-of-interest (ROI) video processing based on low-complexity automatic ROI detection within video frames of video sequences. The low-complexity automatic ROI detection may be based on characteristics of video sensors within video communication devices. In other cases, the low-complexity automatic ROI detection may be based on motion information for a video frame and a different video frame of the video sequence. The disclosed techniques include a video processing technique capable of tuning and enhancing video sensor calibration, camera processing, ROI detection, and ROI video processing within a video communication device based on characteristics of a specific video sensor. The disclosed techniques also include a sensor-based ROI detection technique that uses video sensor statistics and camera processing side-information to improve ROI detection accuracy.

Abstract: The present invention aims to prevent a problem that an image on a document sheet is erased due to misdetection of a line-shaped noise. A copy machine 1 compares RGB values of a target pixel with averaged RGB values (Step S103). If only one of the RGB values has a difference that is greater than a prescribed value Ref2 (Step S103: YES), the copy machine 1 extracts the target pixel as a line-shaped noise pixel, and moves to a line-shaped noise correction (Step S108) while holding the address of the target pixel in a line-shaped noise address storing area 49b. If two of the RGB values have differences (Step S103: NO, Step S104: YES) and a difference between these two of the RGB values is no greater than a prescribed value Ref3 (Step S105: YES), the copy machine 1 extracts the target pixel as a line-shaped noise pixel, and moves to the line-shaped noise correction (Step S108) while holding the address of the target pixel in the line-shaped noise address storing area 49b.

Abstract: Methods (1200), apparatuses, and computer program for finding a region containing text in a colour bitmap image comprising pixels are provided. Connected components (CCs) are generated (1200) from the colour bitmap image by grouping substantially similarly coloured and adjacent pixels. Independently of colour, which of the connected components are text connected components are determined (1212) dependent upon attributes of the generated connected components. For each text CC) a value is assigned (1214) to each tile that comprises at least a portion of the text connected component. The value indicates the presence of text overlapping the tile. Each tile comprises pixels of the colour bitmap image. The region containing text in the colour bitmap image is determined (1216) dependent upon the assigned values of the tiles.

Abstract: A method and system including capturing a video stream including embedded data, segmenting the video stream into a plurality of video frames included therein, locating a color mass, denoted C?, for each color element of every individual video frame of the plurality of video frames by summing color value coordinates for a given color element included in the individual video frame, locating a color mass, denoted C, for each color element of a corresponding individual video frame, the corresponding individual video frame corresponding a video frame which does not include embedded data, subtracting C from C?, and deriving, from a result of the subtraction, a value of a first coordinate and a second coordinate, the first coordinate and the second coordinate including coordinates of a vector, the vector corresponding to a string of bits including information embedded in the individual video frame. Related apparatus, methods and systems are also described.

Abstract: A method of initially estimating a front view portion of a photographed image and separating the photographed image into a front view and a background without user interaction and apparatus performing the method are provided. The method of separating a front view and a background of an image includes dividing one or more pixels included in a photographed image into pixel groups according to color similarity between the pixels, estimating the position of the front view in the image divided into the pixel groups, and separating the front view and the background based on the estimated position of the front view. The method automatically separates the front view and the background of the image without a user input.

Abstract: A method and system is provided for segmenting scanned image data in accordance with mixed raster content processing for more efficient processing of non-uniform color touching objects. The scanned data is segmented to background and foreground layers wherein the foreground layer is comprised of a plurality of objects such as text characters. At least one of the plurality of objects is identified as being non-uniform in color. The non-uniform color object is partitioned into a plurality of sub-objects of predetermined size pixel blocks. The sub-objects are then clustered by uniform color and coded with a binary compression algorithm as a foreground layer segment. Non-uniform color sub-objects are alternatively discarded for compression with the background layer algorithm, or processed for determination of a particular color based upon the color of a plurality of pixels within the sub-object.

Abstract: A method of analyzing a thermal image of a coated substrate to determine the presence of defects includes determining a defect temperature range based on a color of the coated substrate and the maximum temperature of the coated substrate in the thermal image. Thereafter, the thermal image is processed by determining a signal value of a pixel of interest based on a temperature of the pixel of interest, temperatures of pixels in a kernel of pixels surrounding the pixel of interest, and the color of the coated substrate. The signal value of the pixel of interest is then compared to the lower temperature threshold of the defect temperature range, wherein the pixel of interest is a defect location when the signal value of the pixel of interest is greater than or equal to the lower temperature threshold.

Abstract: An image processing apparatus, comprising: a detecting unit that detects a foreground area including a foreground object, a background area, and a boundary area between the foreground area and the background area, from data of a processing target image; and a display control unit that executes a control to display the boundary area in a first color distinguishable from other areas and the background area in a second color different from the first color when the processing target image is displayed.

Abstract: Evaluation and an area to which the evaluation is added are identified in an image, and the image is processed based on a rule for processing the image and the identified evaluation and area.

Abstract: The present invention relate generally to digital watermarking. One claim recites an apparatus comprising: electronic memory for buffering a color video signal comprising a first frame and a second frame; and one or more electronic processors programmed for: transforming a first color channel and a second color channel of the first frame by hiding a digital watermark in the first color channel such that the first digital watermark includes a first signal polarity, and hiding the digital watermark in the second color channel such that the digital watermark includes a second signal polarity that is inversely related to the first signal polarity; transforming a first color channel and a second color channel of the second frame by hiding a digital watermark in the first color channel such that the first digital watermark includes the second signal polarity, and hiding the digital watermark in the second color channel such that the digital watermark includes the first signal polarity.

Abstract: An image processor extracts a pixel area including a pixel of interest for processing and peripheral pixels located around the pixel of interest from input image data, generates a plurality of pixel groups by dividing pixels in the pixel area based on a pixel value distribution in the pixel area, calculates a pixel group similarity between a pixel group and a pixel group including the pixel of interest for each pixel group for pixels belonging to the pixel group in the pixel area, calculates a pixel value similarity of each pixel in the pixel area based on a pixel value of the pixel of interest, calculates filter coefficients to be applied to pixels in the pixel area based on the pixel group and pixel value similarities, and smooths the pixel value of the pixel of interest based on pixel values in the pixel area and the filter coefficients.

Abstract: An image segmentation system selects candidate images from an image collection. Image analysis on individual images proceeds by first detecting salient features on each image. Patches are centered on points of interest located on the salient features of the image. Each patch is gridded into blocks. The block feature vectors are merged to generate a patch feature vector. A fingerprint for each image is obtained by merging patch feature vectors across the image. Images with similar fingerprints are identified and geometric matching is performed to further select images with similar objects. Common regions are tabulated and merged into single regions to segment out coherent objects.

Abstract: Methods and systems for discovering styles via color and pattern co-occurrence are disclosed. According to one embodiment, a computer-implemented method comprises collecting a set of fashion images, selecting at least one subset within the set of fashion images, the subset comprising at least one image containing a fashion item, and computing a set of segments by segmenting the at least one image into at least one dress segment. Color and pattern representations of the set of segments are computed by using a color analysis method and a pattern analysis method respectively. A graph is created wherein each graph node corresponds to one of a color representation or a pattern representation computed for the set of segments. Weights of edges between nodes of the graph indicate a degree of how the corresponding colors or patterns complement each other in a fashion sense.

Abstract: In an exemplary embodiment of the present invention, an automated, computerized method is provided for processing an image. According to a feature of the present invention, the method comprises the steps of providing an image file depicting an image, in a computer memory, identifying information in the image file relevant to a logical deduction regarding material and illumination aspects of an image and selected from information relevant to spatio-spectral aspects of an image and constituents of color; defining a constraint as a function of the information; and utilizing the constraint in an image segregation operation.

Abstract: The compression processing unit 30 of the image processing apparatus makes the color conversion process section 50 to the layout analysis processing section 53 extract the text string region, and makes the foreground layer generating section 54 extract the foreground pixel from the text string region to generate the foreground layer. The line detection process section 52 extracts the line art from the input image data, and removes the pixel block configuring the line art from the foreground pixel-block mask generated by the foreground extracting section 51. The layout analysis processing section 53 estimates the direction of the text string in accordance with the distance of the foreground regions and the number of connected foreground regions, and merges the foreground regions connected in the estimated direction, to extract the text string region.

Abstract: A “Transform Invariant Low-Rank Texture” (TILT) Extractor, referred to as a “TILT Extractor” accurately extracts both textural and geometric information defining regions of low-rank planar patterns from 2D images of a scene, thereby enabling a large range of image processing applications. Unlike conventional feature extraction techniques that rely on point-based features, the TILT Extractor extracts texture regions from an image and derives global correlations or transformations of those regions in 3D (e.g., transformations including translation, rotation, reflection, skew, scale, etc.). These image domain transformations inherently provide information relative to an automatically determinable camera viewing direction. In other words, the TILT Extractor extracts low-rank regions and geometric correlations describing domain transforms of those regions relative to arbitrary camera viewpoints.

Abstract: A method for detecting a shadow of an object in an image is provided. A moving object in a plurality of continuous images is detected. A histogram of a color variation of the moving object in each of the images is calculated. The histograms of the color variation are accumulated to obtain a cumulative histogram. A distribution of the color variation in the cumulative histogram is estimated to obtain a shadow distribution function. Whether each pixel in a received image belongs to the shadow is determined by using the shadow distribution function.

Abstract: The present invention, as evidenced from the drawings and descriptions provided herein, can be characterized in various, different, through unifying, ways. For example, from a methodologic point of view, the invention may be seen as providing a method which (1) procedurally engages a PDF data stream that is en route to printing, (2) determines whether, in that data stream, there is an image-only data file, and (3), if the answer to that determination is Yes, channels that data file into a novel PDF image-only pipeline for expedited pre-printing preparation (image decoding, resizing, rendering, etc.). From a systemic point of view, the invention proposes an interactive and cooperative assembly of structures, as illustrated in the drawing figures, which are constructed specifically to perform the methodologic functions just described.

Abstract: An overall processing time to rasterize, at the first device, the electronic document to be rendered is computed. Also, a rendering time to render, at the first device, the electronic document to be rendered is computed. When the overall processing time to rasterize at the first device is greater than the rendering time to render at the first device, the electronic document to be rendered is parsed into a first document and sub-documents. A productivity capacity of each node is determined, the productivity capacity being a measured of the processing power of the node and the communication cost of exchanging information between the first device and the node. A sub-document is rasterized at a node when a productivity capacity of the node reduces the processing time to rasterize the electronic document to be rendered to be less than the computed overall processing time.

Abstract: An image combining apparatus and a control method for an image combining apparatus that allows a user to write a handwritten image on a writing sheet while confirming the positional relationship between the handwritten image and a photograph to be combined. When a writing sheet having a handwriting area in which a user writes the handwritten image to be combined with a photograph is printed, a reference image generated on the basis of the photograph is printed in the handwriting area.

Abstract: A method and system are disclosed for creating a real-time, high accuracy mosaic from an aerial video image stream by applying orthorectification of each original video image frame using known ground control points, utilizing a photogrammetric model resolving the object image into pixilation, applying shading to the pixellation, and mosaicking the shaded pixilation of several orthorectified images into a mosaicked image where the mosaicked image is then scaled to the known original image dimensions.

Abstract: An image processing apparatus determines an attribute of a block image based on the attribute of the block image determined based on a color distribution characteristic amount of the block image and the attribute of the block image determined based on an edge characteristic amount of the block image.

Abstract: A method, system, and computer-readable storage medium for automatic segmentation of a video sequence. A segmentation shape prediction and a segmentation color model are determined for a current image of a video sequence based on existing segmentation information for at least one previous image of the video sequence. A segmentation of the current image is automatically generated based on a weighted combination of the segmentation shape prediction and the segmentation color model. The segmentation of the current image is stored in a memory medium.

Abstract: A digital camera function, such as can be implemented in a cellular telephone handset, and that includes automated segmentation of foreground subjects in acquired digital photos and images. Successive images are captured by the digital camera function at different flash exposure levels, for example using existing light only and using flash exposure. After alignment and registration of the images, luminance difference values in the two images are determined for each pixel, and the luminance difference values compared against a threshold value on a pixel-by-pixel basis. Those pixels with luminance difference values exceeding the threshold are segmented from the image as foreground subjects.

Abstract: A clustering unit calculates, for clusters in a descending order of the number of pixels belonging thereto, a distance from a feature vector of a processing object pixel and a representative feature vector of an object cluster, and compares the distance with a first threshold. The processing object pixel is stored in a memory or the like as a pixel belonging to an object cluster when the distance is determined to be less than or equal to the first threshold.

Abstract: Systems, methods and apparatus for image processing by classifying pixels are described. In some systems, an exposure control operation is performed according to the pixel classifications. In some cases, the pixels are classified according to a predetermined segmentation of a color space, based on predicted sensor responses.

Abstract: Disclosed herein are methods and systems of efficiently, effectively, and accurately preparing images for a 2D to 3D conversion process by pre-treating occlusions and transparencies in original 2D images. A single 2D image, or a sequence of images, is ingested, segmented into discrete elements, and the discrete elements are individually reconstructed. The reconstructed elements are then re-composited and ingested into a 2D to 3D conversion process.

Abstract: A method of registering a print between print stages in a printing system is provided. The method comprises: printing a first part of a digital image on a substrate with a first print engine, wherein the first part of the digital image includes a plurality of reference features; scanning image content on the substrate as it is readied for the second print engine; determining the actual positions of the reference features; using the actual positions of the reference features to determine desired adjustments for the second part of the digital image; applying electronic registration according to the desired adjustments to modify image content of the second print to be aligned with content already on the substrate; and printing a second part of the digital image on the substrate.

Abstract: A system and method for detecting an area of interest such as a pulmonary embolism in a structure of interest such as a vessel tree or airway tree are provided. The method comprises: segmenting image data of the structure of interest; and rendering two-dimensional images based on a function of the image data and the segmented image data within slabs defined by the segmented image data.

Abstract: The information processing apparatus comprises: an input unit which inputs moving image data of frames; a reference information acquisition unit which acquires reference information in accordance with the moving image data of one of the frames inputted to the input unit, the reference information forming a reference for identifying a constituent part of a person; a constituent part region extraction unit which extracts, in accordance with the reference information, a constituent part region where the constituent part of the person is situated, from the moving image data of each of the frames inputted after the frame from which the reference information has been acquired by the reference information acquisition unit; a priority region setting unit which sets, in accordance with the constituent part region, a priority region in the moving image data of each of the frames inputted after the frame from which the reference information has been acquired by the reference information acquisition unit; and a processin

Abstract: If a pixel of interest on a line of interest is located in an attribute region different from that in which a pixel immediately preceding the pixel of interest is located, the luminance value and color difference values of the pixel of interest are recorded in this order adjacent to data recorded in a data packet set for the line of interest (S811). If the pixel of interest is located in the same attribute region as that in which the preceding pixel is located, the luminance value of the pixel of interest is recorded adjacent to the data recorded in the data packet (S812). The data packet generated by executing the above recording process on each pixel forming the line is output.

Abstract: Described is a bio-inspired vision system for object recognition. The system comprises an attention module, an object recognition module, and an online labeling module. The attention module is configured to receive an image representing a scene and find and extract an object from the image. The attention module is also configured to generate feature vectors corresponding to color, intensity, and orientation information within the extracted object. The object recognition module is configured to receive the extracted object and the feature vectors and associate a label with the extracted object. Finally, the online labeling module is configured to alert a user if the extracted object is an unknown object so that it can be labeled.

Abstract: Exemplary embodiments of color conversion circuits and color conversion methods convert input color data into output color data. The input color data is positioned in a three-dimensional color space, which is divided into a plurality of unit cubes each having a fixed dimension. The input color data is converted by performing interpolations using conversion coefficients at vertexes of the unit cube within which the input color data is positioned. When the input color data is positioned on a gray axis of the color space, a substitution circuit substitutes some of the conversion coefficients such that the interpolation becomes a linear interpolation. As a result, it is assured that input color data positioned on the gray axis is converted to gray output color data.

Abstract: A difference detecting apparatus include: an image receiving unit that receives at least one or more first images and at least one or more second images; and an exception region acquiring unit that acquires (i) first exception regions that include non-background-color pixels of a first common image, (ii) second exception regions that include non-background-color pixels of a second common image, or (iii) both of the first exception regions and the second exception regions. The difference detecting apparatus includes a first difference detecting unit that detects differences between a first image of attention which is at least one of the first images and a second image of attention which is one of the second images corresponding to the first image of attention except for the first exception regions, the second exception regions, or a union or product of sets of the first exception regions and the second exception regions.

Abstract: Provided are an apparatus and method for enhancing image quality of an input image captured by an image capturing device having an aperture with a plurality of openings employing different color filters. The image quality enhancing apparatus includes an ROI (region of interest) classifying unit classifying ROIs according to distances from the image capturing device of a captured input image by using a cluster-based image segmentation algorithm, a color channel registering unit determining motion vectors of color channels corresponding to the respective ROIs by analyzing a high frequency component of image data included in the ROIs, and moving the color channels based on the determined motion vectors to obtain a registered image of the respective ROIs, and an image fusing unit fusing the registered images of the respective ROIs to obtain a fused image.

Abstract: In a case where a background removal level is a level for removing a background, monochrome image data is generated based on color image data and then background removal processing is applied to the generated monochrome image data. In a case where the background removal level is a level for not removing the background, the background removal processing is applied to color image data and then monochrome image data is generated based on the image data having underdone the background removal processing.

Abstract: A method of detecting generally rectangular objects in an image comprises determining candidate rectangles in the image based on detected corners in the image, ranking the candidate rectangles on the basis of a set of differentiating factors and detecting objects in the images based on the ranked candidate rectangles.

Abstract: An image processing apparatus of the present invention includes a detecting unit detecting, among plural fundamental regions set to an image, a fundamental region satisfying a predetermined condition as an appropriate region, a specifying unit specifying adjacent states of fundamental regions excluding the appropriate region among the plural fundamental regions, and a region segmentation unit performing region segmentation on each component included in the image based on the adjacent states of the fundamental regions excluding the appropriate region specified by the specifying unit.

Abstract: An image processing apparatus including: a determining unit that determines whether a background color area of an image data is adjacent to a non-background color area of an image data outside of the background color area, the non-background color area including a pixel having color data of a first color; and a converting unit that converts color data of a pixel in the background color area into the first color when the determining unit determines that the background color area is not adjacent to the non-background color area, and converts the color data of the pixel in the background color area into a second color which is different from the first color when the determining unit determines that the background color area is adjacent to the non-background color area.

Abstract: Restriction information on a total colorant amount for a medium is obtained. Patches at grid points in a color space corresponding to a plurality of colorants at which the total colorant amount falls within a restriction represented by the restriction information, and a patch at a point surrounded by the patches are generated. Color values are obtained by measuring the colors of the patches printed on the medium. It is determined based on a color prediction value between the grid points whether the measured color values are appropriate, and if so, a color value at a grid point at which the total colorant amount exceeds the restriction is estimated based on the measured color values. A color separation table is created based on the measured color values and the estimated value.

Abstract: A method and system of extracting a perceptual feature set for image/video segmentation are disclosed. An input image is converted to obtain a hue component and a saturation component, where the hue component is quantized into a number of quantum values. After weighting the quantized hue component with the saturation component, the weighted quantized hue component and the saturation component are subjected to a statistical operation in order to extract feature vectors. Accordingly, the method and system provide overall segmentation results that are very close to human interpretation.