Abstract: An alpha matte is generated from image forming elements of an image. For each of one or more of the image forming elements: a respective representative foreground value is determined from one or more of the image forming element values; the respective representative foreground value and the value of the image forming element are normalized with respect to a threshold level; and a respective value of the alpha matte is generated from an evaluation of the normalized image forming element value in relation to the normalized representative foreground value.

Abstract: Image matting is performed on an image having a specified foreground region, a background region and an unknown region by selecting a kernel size based on a size of the unknown region. The matting processing is performed using the selected kernel size to provide an alpha matte that distinguishes a foreground portion from a background portion in the unknown region. Further, in some implementations, a trimap of the image may be segmented and matting processing may be performed on each segment using a kernel size appropriate for that segment.

Abstract: A method for automatic food recognition by using portable devices equipped with digital cameras. With this system, it is possible to identify a previously established food menu. To this purpose, a semi-automated method of segmentation is applied to delineate the regions in which each type of food in an image of a plate of food, captured by a user. Pattern recognition techniques are used in images, integrated into a system whose goal is to label each type of food contained in the photo of a plate of food. No type of preprocessing is performed to correct deficiencies in capturing the image, just using the auto-focus component present in the portable device to capture a clear image.

Abstract: An inspection apparatus specifies a region for displaying an advertisement from an image of a virtual space. The inspection apparatus comprises: an image mapping unit that maps an image, which uses a color that is not used in the virtual space and where the display status of the advertisement varies in accordance with a viewpoint of a user, on a region where the advertisement is to be displayed in the virtual space; an inspection image acquiring unit that acquires a virtual space that is actually displayed on a screen on a frame-by-frame basis; and an advertisement region extracting unit operative to extract, by color-filtering the acquired image of the virtual space, a region that is rendered with a color that is not used in the virtual space, as a region for displaying the advertisement perceived by a user.

Abstract: In one embodiment an electronic device comprises an input/output module, a memory coupled to the input/output module, and logic to store a first image of a face in the memory module, associate an identity with the first image of a face, subsequently collect a second image of a face, determine a correlation between features on the first image of a face and the second image of a face, and store the correlation between the first image and the second image. Other embodiments may be described.

Abstract: A user may perform an image search on an object shown in an image. The user may use a mobile device to display an image. In response to displaying the image, the client device may send the image to a visual search system for image segmentation. Upon receiving a segmented image from the visual search system, the client device may display the segmented image to the user who may select one or more segments including an object of interest to instantiate a search. The visual search system may formulate a search query based on the one or more selected segments and perform a search using the search query. The visual search system may then return search results to the client device for display to the user.

Abstract: A method of identifying one or more image features of an image based on content of the image according to one example embodiment includes receiving an image, correcting a distortion and a tone of the image, segmenting the corrected image and extracting the one or more image features, generating an input image descriptor based on the one or more extracted image features, matching the input image descriptor with a reference image descriptor, and performing an action based on the matched reference image descriptor.

Abstract: Subject matter disclosed herein relates to foreground image extraction and image depth of video images.

Abstract: Techniques are disclosed for analyzing a scene depicted in an input stream of video frames captured by a video camera. Bounding boxes are determined for a set foreground patches identified in a video frame. For each bounding box, the techniques include determining textures for first areas, each including a foreground pixel and surrounding pixels, and determining textures for second areas including pixels of the background model image corresponding to the pixels of the foreground areas. Further, for each foreground pixel in the bounding box area, a correlation score is determined based on the texture of the corresponding first area and second area. Pixels whose correlation scores exceed a threshold are removed from the foreground patch. The size of the bounding box may also be reduced to fit the modified foreground patch.

Abstract: An image processing apparatus extracts an area for each color from an illustration area, specifies an area that is in contact with the boundary of the illustration area, extracts a color around the illustration area, determines whether or not the extracted color around the illustration area is the same as the color of the specified area, and processes vector data that represents an area that has been determined as having the same color.

Abstract: A video is segmented to produce volumetric video regions. Descriptors are created for the video regions. A region graph is created for the video, where the region graph has weighted edges incident to video regions and the weight of an edge is calculated responsive to the descriptors of the video regions incident to the edge. The region graph is segmented responsive to the weights of the edges incident to the video regions to produce a new region graph having new volumetric video regions comprised of merged video regions of the first region graph. The descriptions of the region graphs are stored in a data storage.

Abstract: When an operator starts a pattern separation extraction tool, an input screen is displayed on the display device. The operator can choose and designate any one of document image data within the storage device through the input screen. The document image that is chosen by the operator is displayed on the display device. The operator can choose and designate a color sample by a drag operation on the document image that is displayed on the display device. If the operator inputs the designation to finish the designation of a color sample through the input device after designating some color samples, the pattern separating extraction device generates and outputs the image data that consists of one print pattern for each of the print patterns included in the document image chosen by the operator.

Abstract: There are provided a foreground region extraction program, a foreground region extraction apparatus, and a foreground region extraction method capable of clipping an object region (foreground region) at high speed. An arrangement is as follows: Foreground pixels designated by a user and background pixels designated thereby are each set as a reference pixel to identify, from among a plurality of divided color spaces created by a three-dimensional color space being divided, the divided color space to which each of the reference pixels belongs, as a reference divided color space.

Abstract: An unprocessed image is prepared which is shot against an arbitrary background, including materials to be trimmed. Color values are collected from a plurality of frames of this unprocessed image in a collection point including one or more pixels, whereby a color information set is obtained. From the color information set, it is judged which color shows the background and which color shows the materials to be trimmed, thereby determining an optimum background-side color value. This process is applied to an area where to extract the background from, thereby obtaining a background image into which the background is extracted. This makes it possible to obtain background images from unprocessed images that are shot in busy locations, without traffic controls or dedicated studios.

Abstract: The present invention relates to an image processing apparatus and method, and a program that are capable of more appropriately evaluating the image-capture state of an image. A blur degree score calculation unit 23 through to a chroma score calculation unit 27 extract a feature quantity of a pre-specified feature from an input image, and calculate a feature-by-feature score indicating an evaluation for the input image on the basis of the feature. For example, the luminance score calculation unit 24 extracts, as a feature quantity, a luminance value from the input image, and calculates a luminance score indicating an evaluation based on the distribution of the luminance values in the subject portion of the input image. The overall score calculation unit 28 calculates an overall score indicating the evaluation of the image-capture state of the input image from each feature-by-feature score.

Abstract: One embodiment of the present invention sets forth a technique for compressing color data. Color data for a tile including multiple samples is compressed based on an equality comparison and a threshold comparison based on a programmable threshold value. The equality comparison is performed on a first portion of the color data that includes at least exponent and sign fields of floating point format values or high order bits of integer format values. The threshold comparison is performed on a second portion of the color data that includes mantissa fields of floating point format values or low order bits of integer format values. The equality comparison and threshold comparison are used to select either computed averages of the pixel components or the original color data as the output color data for the tile. When the threshold is set to zero, only tiles that can be compressed without loss are compressed.

Abstract: The grayscale of an input signal is converted without amplifying noise components thereof. A grayscale conversion portion performs grayscale conversion on an input signal IS to create a converted signal TS, a noise reduction degree determining portion determines a noise reduction degree NR that expresses a strength of noise reduction processing to be applied to the converted signal based on the input signal IS and the converted signal TS, and a noise reducing portion executes noise reduction processing on the converted signal TS based on the noise reduction degree NR. By doing this, it is possible to convert the grayscale of the input signal without enhancing the noise.

Abstract: Methods disclosed permit compositing operations to be performed on images using an associated mask even in situations where the image and the mask differ in size. In some embodiments, image and mask data may be specified as a soft mask image in a page description language such as PDF. Scaling operations may be performed on the image, mask, or on both the image and mask when they differ in size. Compositing operations may be performed on the scaled image and/or mask after they have been scaled to the same size. Composting operations in situations where the original mask and image are of the same size are not affected by scaling operations.

Abstract: A method for displaying a segmented two-dimensional (2D) image includes obtaining a three-dimensional (3D) volume dataset corresponding to an imaged volume along a viewing plane, segmenting an object of interest within 3D volume to generate a plurality of segmented two-dimensional (2D) images along the viewing plane, selecting a reference image for viewing from the plurality of segmented 2D images, and displaying the reference image, the reference image having a first segmentation boundary drawn around the object of interest and a second segmentation boundary drawn around the object of interest, the first segmentation boundary being derived from the segmentation performed on the reference image and the second segmentation boundary being derived from the segmentation performed on at least one non-reference image of the plurality of segmented 2D images.

Abstract: An image processing device includes a processor and a memory. The memory stores computer-readable instructions therein. The computer-readable instructions, when executed by the processor, causes the image processing device to perform: acquiring image data indicative of an image including an object image and a background image adjacent to the object image, the object image and the background image defining a border region in a border of the object image and the background image; acquiring at least two of a first characteristic value, a second characteristic value, and a brightness of the border region, the first characteristic value relating to a color of the object image, the second characteristic value relating to a color of the background image; and correcting a color of the border region by using the at least two of the first characteristic value, the second characteristic value, and the brightness of the border region.

Abstract: Systems and methods for detecting visual objects by employing multiple cues include statistically combining information from multiple sources into a saliency map, wherein the information may include color, texture and/or motion in an image where an object is to be detected or background determined. The statistically combined information is thresholded to make decisions with respect to foreground/background pixels.

Abstract: In an image processing apparatus for carrying out a plurality of correction processes on an input image, a multi-dimensional histogram of the input image is calculated, and a feature amount of the input image for which a specific correction process has been carried out is analyzed based on the multi-dimensional histogram. Then, based on the result of the analysis, correction parameters to be used for another correction process are calculated.

Abstract: A computer-implemented image processing method includes: receiving, using at least one processing circuit, a plurality of image frames of a video; constructing, using at least one processing circuit, a plurality of statistical models of the plurality of image frames at a plurality of pixel granularity levels; constructing, using at least one processing circuit, a plurality of probabilistic models of an input image frame at a plurality of channel granularity levels based on the plurality of statistical models; merging at least some of the plurality of probabilistic models based on a weighted average to form a single probability image; and determining background pixels, based on a probability threshold value, from the single probability image.

Abstract: A red-eye detection and correction method comprises computing a first difference image based on a difference between red pixel intensity and green pixel intensity of a set of pixels (702). The set of pixels are associated with a first eye region of an image. The method further comprises processing the first difference image for computing at least one gradient and at least one projection associated with the at least one gradient (704). Furthermore, the method comprises determining at least one central point based on the at least one projection (706); and thereafter computing the first eye color defect region based on the at least one central point and a plurality of red pixels of the set of pixels (708). The method also comprises mapping an eye color defect location information computed from a low resolution image to be applicable on the original high resolution image, thereby avoiding recomputation.

Abstract: Methods and systems are provided allowing for background identification and gesture recognition in video images. A computer-implemented image processing method includes: receiving, using at least one processing circuit, a plurality of image frames of a video; constructing, using at least one processing circuit, a plurality of statistical models of the plurality of image frames at a plurality of pixel granularity levels; constructing, using at least one processing circuit, a plurality of probabilistic models of an input image frame at a plurality of channel granularity levels based on the plurality of statistical models; merging at least some of the plurality of probabilistic models based on a weighted average to form a single probability image; determining background pixels, based on a probability threshold value, from the single probability image; and determining whether the plurality of image frames, when examined in a particular sequence, conveys a gesture by the object.

Abstract: A safety system for an ice and liquid dispenser of a refrigerator is used to sense the presence of human skin in a dispensing well. The safety system includes a digital image capture device focused on a dispenser well for capturing images of objects, such as hands, in the dispenser well and a digital image analyzer operatively coupled to the digital image capture device. The digital image analyzer evaluates the digital images captured by the digital image capture device to determine if human skin color is detected in the image of the object in the dispensing well. If human skin color is detected, thus indicating a hand in the dispensing area, any dispensing operation will be prevented and an alert will be provided.

Abstract: A print data generating device comprises a retrieving unit, a bar code data generating unit, and a print data generating unit. The retrieving unit is configured to retrieve image data of an original image. The bar code data generating unit is configured to generate, based on the image data of the original image, data of at least one bar code that stores the original image. The print data generating unit is configured to generate, based on the image data of the original image and the data of the at least one bar code, print data of a print image that includes the at least one bar code arranged on one page and the original image arranged on one or more pages.

Abstract: An electronic document generation system includes a first layer generation unit that generates a character image layer that represents a character image in the scanned image by a predetermined number of bits, an edge image generation unit that generates an edge image of the character image, a second layer generation unit that generates an antialiasing layer that includes a binarized image generated based on the edge image and that is to be superimposed in a semi-transparent state on the character image layer, a file generation unit that generates the electronic document that includes the character image layer and the antialiasing layer, and a base color determination unit that determines a base color of the character image. The second layer generation unit sets the same color as the base color for the antialiasing layer.

Abstract: A subject position determination method includes: generating a plurality of binarized images of a target image based upon color information or brightness information of the target image; calculating an evaluation value used to determine a subject position in the target image for each of the plurality of binarized images; and determining a subject position in the target image based upon the evaluation value.

Abstract: A method for producing a three-dimensional image (70) of an object. The method includes providing a model (8) of the object (62) (200), insonifying regions of the object from source transducers (58) external to the object (62) (202), receiving return echoes from the object (62) at receiving transducers (58) external to the object (62), processing the return echoes (204) and generating a hybrid image (70) of the object (62) comprising object regions responsive to the model (8) of the object (62) and object regions responsive to the return echoes (208/212).

Abstract: Embodiments disclosed include methods for connected component labeling including labeling groups of raw data as one or more regions, the labeling including designating one or more data structures as containing information about the one or more regions; designating one or more of the regions as one or more subregions to expose a spatial distribution of one or more region features; and arranging at least one memory array with a 1:1 correspondence to a data array associated with the raw data to enable one or more data structures to include feature labels of the one or more subregions, the 1:1 correspondence enabling acquisition of the one or more region features with a controllable precision.

Abstract: The present invention relates to an image processing apparatus and method, and a program that are capable of more easily identifying an area of a subject in an image. A luminance information extraction unit 21 through to a motion information extraction unit 25 extract predetermined information from an input image and create an information map indicating feature quantities of features possessed by an area of a subject of the input image. Furthermore, the luminance information extraction unit 21 through to the motion information extraction unit 25 subtract an average value of the pixel values of the pixels of the entire information map from the pixel value of each pixel of the created information map so as to normalize the information map. As a result, the information map can be normalized, and noise can be removed with a simple process when compared to a case in which the information map is normalized using a DOG filter.

Abstract: A print-document conversion apparatus includes a conversion-module activation section that activates, as a process, a conversion module for performing conversion processing for converting print-document data which is described in a page description language and which includes units of processing into print-image data. The conversion module includes a thread activation part, an assigning part, and a shared cache. The thread activation part activates conversion processing threads. The assigning part assigns the units of processing to the conversion processing threads, and causes the conversion processing threads to perform processing on the units of processing. The shared cache is shared by the conversion processing threads. When a conversion result obtained by converting an object included in the units of processing is stored in the shared cache, each of the conversion processing threads obtains the stored conversion result instead of obtaining the conversion result by converting the object.

Abstract: An image forming apparatus includes an image forming unit that performs image formation on the basis of a plurality of pieces of image data for different colors, the pieces of the image data being generated by a higher-level device; a plurality of data storage units that receive the respective pieces of the image data transferred from the higher-level device via a plurality of first transfer paths corresponding to the respective pieces of the image data, and store therein the respective pieces of the image data; and a control unit that receives control information, which is used for controlling the image formation, from the higher-level device via a second transfer path and controls the data storage units on the basis of the control information so that the data storage units receive and storage therein the respective pieces of the image data transferred from the higher-level device.

Abstract: An image quality evaluation device is disclosed in the present invention, including: an image analyzer, adapted to analyze the parameters of an image to obtain parameter values; and an evaluation unit, adapted to evaluate the quality of an image based on parameter values in line with the predetermined standard and generate the evaluation result. An image quality evaluation method is disclosed in the present invention, including: analyze the parameters of an image to obtain parameter values; and evaluate the quality of an image based on parameter values in line with the predetermined standard and generate the evaluation result. An image quality evaluation device and method provided in the present invention are used to analyze the parameters of an image with the image recognition technology to obtain parameter values and then generate the parameter values in line with the predetermined standard.

Abstract: Systems and methods are provided for demoting color data associated with at least one entity, wherein the entity comprises at least one sub-entity. The at least one sub-entity may be marked as demotable, if the color data associated with the at least one sub-entity is demotable. The at least one entity may be marked as demotable, if all sub-entities enclosed in the at least one entity are demotable. The color data of at least one marked rasterizable entity may be demoted, wherein the at least one marked rasterizable entity may be selected from a set comprising of marked entities and marked sub-entities.

Abstract: A method and an apparatus for multi-label segmentation of an image are described. In a first step user defined labels are determined for one or more pixels of the image. Then a fraction of the pixels of the image for which no user defined label is determined is pre-initialized. Finally, a cellular automaton-based segmentation of the image is performed using the user defined labels and the pre-initialized pixels.

Abstract: A system for providing augmented reality detects foreground occluders in an image of a video stream. One or more virtual objects are then rendered appropriately with respect to the occluders. Location information associated with the image is used to retrieve a three dimensional representation of the location where the image was taken. Features that are expected to appear in the image based on the three dimensional location but that cannot be located are used to determine regions of the image that are likely to include foreground occluders. Pixels in these regions are used to train a color model that classifies pixels as either part of the background of the image or part of one or more foreground occluders. The pixels in the image are classified using the model, and one or more virtual objects are rendered so that they appear behind any foreground occluders.

Abstract: A similar shader search apparatus using image feature extraction includes: an image extraction unit configured to classify color, texture, pattern features of a 2D image, into a color feature set, a texture feature set, and a pattern feature set, numerically analyze the respective feature sets, and extract a feature value of the image; a shader extraction unit configured to analyze a predetermined stored shader, classify features having an effect upon color, texture, and pattern into a color feature set, a texture feature set, and a pattern feature set, numerically analyze the respective feature sets, and extract a feature value of the shader; and a distance function calculation unit configured to receive the image feature value and the shader feature value, calculate the similarity of color between the image and the shader, and calculate the similarity of texture between the image and the shader using the Euclidean distance function.

Abstract: A method for detecting edge pixels in an image plane based on intensity and neutrality of a current pixel is provided. The method includes detecting the edge pixels in the image plane based on predetermined criteria. The predetermined criteria determining whether: (a) a difference between the maximum value and the minimum value of the specified characteristic is greater than or equal to a predetermined threshold; and (b) (i) a difference between a current value and the minimum value of the specified characteristic, or (ii) a difference between a current value and the maximum value of the specified characteristic is greater than or equal to a predetermined threshold. The predetermined thresholds are determined based on intensity and neutrality of the current pixel.

Abstract: The present invention relates to a method and apparatus for processing a scanned image. The method for processing a scanned image comprises: a shaded region extracting step of extracting a region, which is shaded by a shading object and lies in a margin in the vicinity of an edge of the scanned image, as a shaded region; and a pixel value repairing step of repairing values of pixels, which lie both in a line segment and the shaded region, by using a linear model according to known values of pixels, which lie both in the line segment and the margin, the line segment passing through the shaded region and being parallel to the edge.

Abstract: An image processing device including: a color space selection unit that selects a color space based on designated color information; and a region specifying unit that specifies a region that includes a color that matches the color that is shown by the color information designated in the color space from a color region specified image that is provided for color region specification.

Abstract: An image forming apparatus includes a classifying unit which classifies constituent elements constituting print data into a single or a plurality of areas based on a plurality of types of the constituent elements; a color conversion processing unit which performs, with respect to each of the constituent elements classified by the classifying unit, a color conversion coping with each type the constituent elements; and an image forming unit which composes the constituent elements subjected to the color conversion by the color conversion processing unit and forms an image based on the print data composed.

Abstract: A system and method for normalizing and codifying divergent color systems into a single universal color system. The middleware engine receives a data feed comprising a plurality of color swatches or images from one or more merchant system and normalizes the data feed into a common format. The dominant processor extracts the product images from the normalized data, segments each product image into segments, determines a dominant color for each segment, and determines the dominant product color for each product image based on prevalence of the dominant product color in each segment. The matched color processor converts the determined dominant product color into a digital value of the universal color system based on the color component intensity values.

Abstract: An image processing apparatus includes a first extraction unit, a second extraction unit, a third extraction unit, a determination unit, a correction unit, and a color quantization unit. The first extraction unit extracts from an image a region and color of an information image. The second extraction unit extracts a color of a peripheral image surrounding the extracted region. The third extraction unit extracts information necessary for color quantization processing. The determination unit determines whether a color difference between the extracted color of the information image and the extracted color of the peripheral image falls within a predetermined range when color quantization processing is based on the extracted information. The correction unit corrects a representative color if it is determined that the color difference does not fall within the predetermined range. The color quantization unit performs color quantization processing on the image on the basis of the corrected representative color.

Abstract: An image information processing system, which processes image information of a customer wearing products, includes: a customer information database, storing customer information in association with customer code information; and a product information database, enabling storage of product information, concerning the products that the customer wears, in association with order code information. Acquisition of the image information of the customer in the state of wearing products is enabled by a digital camera, and by means of a trial fitting catalog preparation process, a trial fitting catalog, in which the image information acquired by the digital camera unit are included with the customer code information of the customer, who wore the products, and the order code information on the products, is prepared and output by a printer.

Abstract: An image processing apparatus according to the present invention determines a monochrome area and a color area of an input image. The apparatus comprises an acquisition unit that acquires an image characteristic value of the input image; and a determination unit that determines whether each pixel group in the input image is a monochrome area or a color area based on the image characteristic value acquired by the acquisition unit, wherein the acquisition unit acquires a plurality of image characteristic values corresponding to a plurality of acquisition areas including a determination target pixel group, and the determination unit determines whether the pixel group is a monochrome area or a color area based on the plurality of image characteristic values corresponding to the plurality of acquisition areas including the pixel group.

Abstract: An image processing apparatus may create text image data representing a text image, based on target image data representing a target image including text. The image processing apparatus may determine an extended text area in the target image based on information related to a sharpness of the text included in the target image. The extended text area may include a text area corresponding to pixels constituting text in the text image represented by the created text image data, and also include a surrounding area around the text area. The image processing apparatus may change a color of the extended text area to a color of a background of the target image to create background image data.

Abstract: An image processing apparatus according to the present invention comprises: an acquisition unit that acquires a statistical value of pixel values for each divided region; a determination unit that compares for each divided region the statistical value of the divided region acquired by the acquisition unit with a first threshold and determines whether the divided region is as color region or a monochrome region; and a re-determination unit that compares a statistical value of an adjacent divided region with a second threshold, by which a divided region is more likely determined as a color region than by the first threshold, for each adjacent divided region, and re-determines whether the adjacent divided region is a color region or a monochrome region.

Abstract: An image processing device includes a processor configured to perform: acquiring target image data representing a target image; and generating binary image data representing the letter in the target image by using the target image data. The generating of the binary image data comprises: identifying a background color value representing color of background of the target image; identifying a letter color value representing color of the letter in the target image; acquiring a difference between the background color value and the letter color value, the difference including a plurality of component differences; selecting one specific component image data corresponding to a specific component from among the plurality of components, the specific component corresponding to a maximum component difference among the plurality of component differences; and performing a binarizing process on the selected one specific component image data to generate one binary image data.