Abstract: A color-unevenness inspection apparatus includes: an image pickup section picking up an image of an inspection target in a color-unevenness inspection; and an image generation section generating an uneven-color image by, in the picked-up image of the inspection target obtained by the image pickup section, calculating a chroma in each unit region and identifying an uneven-color region based on a magnitude of the calculated chroma. The color-unevenness inspection apparatus further includes: a calculation section calculating, for the uneven-color region in the uneven-color image, an evaluation parameter to be used in the color-unevenness inspection; and an inspection section performing the color-unevenness inspection based on the calculated evaluation parameter. The image generation section calculates the chroma, in each unit region of the picked-up image, while performing correction processing that reflects variations in color-unevenness visibility from color to color.

Abstract: There are provided methods and systems for use in performing feature sensitive captioning of media content. In one implementation, such a method includes detecting an aesthetically determinative feature of a media content unit selected by a user, and determining a captioning aesthetic for a caption of the media content unit based at least in part on the aesthetically determinative feature. The captioning aesthetic may include a background aesthetic and a text aesthetic. The captioning aesthetic may be utilized by a feature sensitive captioning application to produce a feature sensitive caption for the media content unit.

Abstract: A image input means 81 inputs a lifeform image which is a captured image of a lifeform sample. A structure standard color storage means 82 stores a standard color of a structure included in the lifeform image. A structure extraction means 83 extracts a target structure from the lifeform image. A structure color computation means 84 computes, from an image of the structure extracted by the structure extraction means 83, a color of the structure. A color distribution conversion means 85 converts a color distribution of the input lifeform image so that a difference between the color of the structure computed by the structure color computation means 84 and the standard color of the corresponding structure stored in the structure standard color storage means 82 is reduced.

Abstract: An image processing apparatus includes a small area divider that divides, on the basis of edge information of an image, the image into multiple small areas each including multiple pixels; an attribute probability estimator that estimates attribute probability for each of the small areas, which is probability that the small area is attributed to a specific area to be detected; an adjacent-small-area connection strength calculator that calculates connection strength that quantitatively indicates a degree to which small areas adjacent to each other among the multiple small areas are attributed to the same area that is the specific area or a non-specific area; and a specific area detector that detects the specific area on the basis of the attribute probability and the connection strength.

Abstract: A computing device is described herein that is configured to select a pixel pair including a foreground pixel of an image and a background pixel of the image from a global set of pixels based at least on spatial distances from an unknown pixel and color distances from the unknown pixel. The computing device is further configured to determine an opacity measure for the unknown pixel based at least on the selected pixel pair.

Abstract: Techniques for creating and manipulating software notes representative of physical notes are described. A note management system comprises a sensor configured to capture an image data of a physical note, wherein the note is separated into one or more segments using marks, wherein each of the segments is marked by at least one of the marks. The note management system further comprises a note recognition module coupled to the sensor, the note recognition module configured to receive the captured image data and identify the marks on the note, and a note extraction module configured to determine general boundaries of the one or more segments within the captured image data based on the identified marks and extract content using the general boundaries, the content comprises content pieces, each of the content pieces corresponding to one of the one or more segments of the note.

Abstract: A self-adaptive image-based obstacle detection method comprises steps: capturing an original image; transforming the original image to an HSV color space, and retrieving a hue component (H) and a saturation component (S) of the HSV color space to form an HS-based image; dividing the HS-based image into image blocks; selecting one image block as a background block; using an obstacle recognition equation to determine whether each of the image blocks is similar to the background block; if no, deleting the image block; if yes, preserving the image block to form a binary obstacle image; and overlaying the binary obstacle image on the original image to filter out the background and obtain an initial ambit of an obstacle image. Then, three orderly movement flow equations are used to determine whether it is an obstacle.

Abstract: The present invention describes enhancing image contrast comprising the following steps: determining a segmentation point according to at least one segmentation threshold and pixel statistical data of a picture, wherein the segmentation point is utilized to divide the pixel statistical data into a first partial statistical data and a second partial statistical data; and determining a first partial brightness conversion function and a second partial brightness conversion function according to the first and the second partial statistical data, respectively. The first partial brightness conversion function is used to adjust brightness values of multiple pixels in the picture corresponding to the first partial statistical data, and the second partial brightness conversion function is used to adjust brightness values of multiple pixels in the picture corresponding to the second partial statistical data.

Abstract: An image processing apparatus comprises: a unit configured to generate a gradation cluster by determining color regions belonging to the same gradation among a plurality of color regions using gradation attribute of boundary, and to generate gradation cluster information including information about a color region belonging to the generated gradation cluster and a gradation type of the gradation cluster; a unit configured to generate a gradation parameter for each gradation region using the color region, the color gradient information, and the gradation cluster information; a unit configured to integrate color regions belonging to the same gradation using the gradation cluster information; and a unit configured to generate a contour vector description based on a color region after integration, and to generate vector data of the gradation region based on the contour vector description and the gradation parameter.

Abstract: A color gamut of image data is appropriately subjected to a smoothing processing to print an image of favorable color reproduction and gradation reproduction. Specifically, when an average lightness is equal to or lower than a blacking lightness, the object pixel is not subjected to the smoothing processing. This can conserve the signal value of the object pixel to prevent a pixel originally having a signal value higher than the blacking lightness from being converted by the gamut compression to a black point. In this manner, a pixel for which the object pixel has the average lightness equal to or lower than the blacking lightness is blacked and a pixel having a signal value higher than the blacking lightness is not compressed to the black point. The resultant image has no deteriorated gradation characteristic when being macroscopically observed.

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: A system and method for color accuracy checking is discussed. In one embodiment, areas within a document are selected for color-checking. A confirmation is made that a second printing of the document has color values which deviate within tolerances from color values of a first printing of the document within each of the selected areas.

Abstract: The present invention relates to a system for providing a supplementary service by identifying an object in an image and comprises: an image service server and a user terminal. The image service server provides image information and includes a database that manages metadata for the provision of the service. The user terminal dynamically generates control command information according to the information for the object selected in the image. In addition, the user terminal receives the information for the object selected in the image that is displayed on screen and transfers the information to the image service server. Furthermore, the user terminal receives from the image service server the preset supplementary service that corresponds to the information for the object selected.

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 feast 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: Methods and systems are provided allowing for background identification 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; and determining background pixels, based on a probability threshold value, from the single probability image.

Abstract: An image processing apparatus includes a calculating unit, an edge-position detecting unit, an identifying unit, and a subject-region detecting unit. For each color separation image, the calculating unit calculates a gradient direction of an edge gradient and an edge intensity at each position on the basis of a color captured image. The edge-position detecting unit detects edge positions in each color separation image on the basis of the gradient directions of the edge gradients and the edge intensities. For each position, the identifying unit identifies the gradient direction of the edge gradient and the edge intensity at the position in one of the plural color separation images that includes the largest edge intensity at the position. The subject-region detecting unit detects a subject region on the basis of the detected edge positions, the identified gradient directions of the edge gradients, and the identified edge intensities.

Abstract: A system and process is provided for the conversion of a stream of two-dimensional images into a pair of streams of images for providing the perception of a stream of three-dimensional images. Each complimentary image in the image stream undergoes the application of a selection and remapping process to independently alter portions of the image, so that the remappings shift the image elements in a manner which produces a stereo depth effect when the images are viewed through the appropriate viewing device.

Abstract: Foreground objects of interest are distinguished from a background model by dividing a region of interest of a video data image into a grid array of individual cells that are each smaller than that a foreground object of interest. More particularly, image data of the foreground object of interest spans a contiguous plurality of the cells. Each of the cells are labeled as foreground if accumulated edge energy within the cell meets an edge energy threshold, if color intensities for different colors within each cell differ by a color intensity differential threshold, or as a function of combinations of said determinations in view of one or more combination rules.

Abstract: Edge enhancement processing is executed by obtaining a sum of whiteness degrees around a target pixel, to which edge enhancement is to be applied, and by adjusting the amount of edge enhancement such that the degree of edge enhancement decreases as the sum of whiteness degrees increases, and the degree of edge enhancement increases as the sum of whiteness degrees decreases. A whiteness degree is a value indicating the extent to which a pixel is close to white, and a sum of whiteness degrees indicates the extent to which the color around the target pixel is whitish.

Abstract: A multilevel image segmentation technique using graph cuts is disclosed. A reduced resolution image is generated from a full resolution image which is to be segmented. The reduced resolution image is then segmented in order to identify a boundary between an object and a background within the image. The identified boundary then identifies a portion of an increased resolution image which is segmented in order to refine the earlier identified boundary. The steps may be iterated for successively increasing image resolutions in order to refine the boundary as required by a particular application. An initial identification of object and background portions of the image may be provided as input by a user. Alternatively, a user may identify only the object portion, and the background portion may be automatically determined.

Abstract: An image processing method for removing a moving object includes an input step of inputting input images; a matching step of matching the input images according to corresponding positions; a determining step of determining a background image from the input images; a marking step of marking at least one moving object from at least one of the input images; and a replacing step of replacing a region, occupied by the moving object in at least one of the input images with a corresponding regional background in another input image.

Abstract: A color erasing apparatus includes a conveyance member to convey a sheet on which an image is formed of a color erasable coloring material, a color erasing part to erase a color of the coloring material of the image formed on the sheet conveyed by the conveyance member, a control part that counts the processed number of sheets images of which are color-erased by the color erasing part and determines whether the processed number of sheets exceeds a previously set threshold, and a notification interface to output a signal for notifying that, cleaning of the color erasing part is required if the processed number of sheets exceeds the threshold.

Abstract: An image retrieval method applies an application server, one or more calculating servers, and a sorting server to perform image retrieval. The application server extracts visual features of an exemplary image. The one or more calculating servers calculate similarities of available images according to the visual features of the exemplary image. The sorting server sorts the available images according to the similarities so as to obtain images similar to the exemplary image.

Abstract: A method for identifying a set of key video frames from a video sequence comprising extracting feature vectors for each video frame and applying a group sparsity algorithm to represent the feature vector for a particular video frame as a group sparse combination of the feature vectors for the other video frames. Weighting coefficients associated with the group sparse combination are analyzed to determine video frame clusters of temporally-contiguous, similar video frames. A set of key video frames are selected based on the determined video frame clusters.

Abstract: Separations or images relating to film or other fields may be registered using a variety of features, such as, for example: (1) correcting one or more film distortions; (2) automatically determining a transformation to reduce a film distortion; (3) applying multiple criteria of merit to a set of features to determine a set of features to use in determining a transformation; (4) determining transformations for areas in an image or a separation in a radial order; (5) comparing areas in images or separations by weighting feature pixels differently than non-feature pixels; (6) determining distortion values for transformations by applying a partial distortion measure and/or using a spiral search configuration; (7) determining transformations by using different sets of features to determine corresponding transformation parameters in an iterative manner; and (8) applying a feathering technique to neighboring areas within an image or separation.

Abstract: An image processing apparatus includes an achromatization determination portion, an achromatization processing portion, and a line designation portion. If a black pixel is present within a predetermined peripheral range from a target pixel in a sub-scanning direction, the achromatization determination portion determines whether to achromatize the target pixel, on the basis of an attribute of a background determination pixel present in an opposite direction from the target pixel with respect to the black pixel and within a range of a predetermined number of pixels from the black pixel. If no black pixel is present within the predetermined peripheral range from the target pixel in the sub-scanning direction, the achromatization determination portion determines not to achromatize the target pixel.

Abstract: The invention provides a method for determining interpolating direction for color demosaicking. In the method, edge information of each pixel of an image captured by a color filter array is first obtained. Then, a highly horizontal level and a highly vertical level of each pixel are determined. An interpolating direction of each pixel is determined based on the edge information, the highly horizontal level and the highly vertical level of the pixel.

Abstract: An image processing apparatus includes an extraction unit and a calculation unit. The extraction unit extracts a local color displacement that is a local displacement of color in a region of interest in a given image. The calculation unit calculates a similarity between the local color displacement and an extracted-color displacement that is a displacement of a preset color.

Abstract: A color display has continuous areas of a single color covering a plurality of sub-pixel electrodes. Each sub-pixel of a given color has sub-pixels of the same given color disposed along at least two of its adjacent edges. Each area of a single color may cover a 2×2 array of sub-pixel electrodes. The colors used may be red/green/blue/white (RGBW), red/green/blue/yellow (RGBY), or orange/lime/purple/white.

Abstract: A method for processing a picture is disclosed. The method according to the invention comprises: segmenting the picture into a background layer and at least another layer; selecting a background template of color harmony for the background layer; determining one template of color harmony for each of the at least another layer from the background template of color harmony depending on the distance between the background layer and said at least another layer. processing the picture by mapping the colors of each segmented layer using the corresponding template of color harmony.

Abstract: A system for segregating handwritten information from typographic information on a document may include a memory, an interface, and a processor. The memory stores an electronic document image of a document where the electronic document image includes pixels and each pixel has a characteristic. The processor may receive, via the interface, the electronic document image and may identify first, second and third most frequently occurring characteristics of the pixels of the electronic document image. The pixels having the first most frequently occurring characteristic represent a background of the document. The processor may determine the typographic information of the document as represented by pixels having the second most frequently occurring characteristic. The processor may determine the handwritten information of the document as represented by pixels having the third most frequently occurring characteristic.

Abstract: Image analysis includes: determining, using one or more processors, an image quality score associated with an image, including: determining a foreground and a background in the image; calculating a set of one or more characteristic parameters of the image based on the determined foreground and background; calculating the image quality score based at least in part on the set of characteristic parameters, wherein calculating the image quality score comprises using an image quality computation model that has been pre-trained; and in response to a search query, generating a set of search results that includes a set the images, wherein inclusion of the images or ranking of the search results is based at least in part on image quality scores associated with the set of images.

Abstract: A person's region is detected from input video of a surveillance camera; a person's direction in the person's region is determined; the separability of person's clothes is determined to generate clothing segment separation information; furthermore, clothing features representing visual features of person's clothes in the person's region are extracted in consideration of the person's direction and the clothing segment separation information. The person's direction is determined based on a person's face direction, person's motion, and clothing symmetry. The clothing segment separation information is generated based on analysis information regarding a geometrical shape of the person's region and visual segment information representing person's clothing segments which are visible based on the person's region and background prior information.

Abstract: A device to apply detection schemes to texture information of a face detected within an image to generate mouth corner candidates and identify best matching mouth corners by applying a geometric model to the moth corner candidates.

Abstract: A method of extracting the dominant colors from a set of target images and storing those colors in a database is described. A method of comparing colors stored in a database with a set of colors extracted from a query image. Also, a method of comparing colors stored in the database with a set of colors defined by a user using a color picker. The user defined colors may or may not include a wildcard color. The list of matching database images may or may no be filtered using metadata.

Abstract: Disclosed are an apparatus and a method for reinspecting a prescription drug, which reinspect the defect state of a defective drug pack after the defect state of an individually packaged drug has been inspected by analyzing the image of the drug. The apparatus includes a drug pack information transceiving module to receive primary inspection data, a drug reinspection controlling module to control a procedure of reinspecting a defect state of a drug pack which has been primarily determined as a defective drug pack, an image processing module to photograph the drug pack, which has been primarily determined as the defective drug pack, and to process an image of the drug pack, and a defect analyzing module to determine a defect state of the drug by analyzing a drug contained in the image of the drug pack provided from the image processing module.

Abstract: An image data processing device processes structured image data including background image data representing a background image, foreground image data representing a foreground image indicating a color and a gross shape, and mask data representing a mask image specifying a prescribed area of the foreground image to be overlaid on the background image. The image data processing device lightens a shade of the background image by applying background color lightening processing to the background data, and lightens a shade of the foreground image less than the shade of the background image by applying foreground color lightening processing to the foreground data.

Abstract: Some embodiments provide a method for editing an image. For a displayed image, the method draws a partial boundary based on movement of a cursor over the image. The partial boundary does not fully divide the image into a region of interest and a second region. Upon completion of the cursor movement, the method automatically extends at least one end of the boundary in order to divide the image into the region of interest and the second region. The method applies edits (e.g., color correction) to only the region of interest of the image. In some embodiments, automatically extending at least one end of the boundary involves (i) extending one or both of the ends to points at which the boundary ends intersect borders of the image and (ii) connecting the boundary from the intersection points along the borders of the image.

Abstract: Methods, apparatus, and computer-readable storage media for fast adaptive edge-aware matting in which a matting technique adaptively feathers selections, provides smooth color correspondence matting, and performs well in textured regions. The matting technique may require fewer strokes and less parameter tuning than conventional matting techniques. The matting technique may have two components implemented in a matting pipeline. A color similarity component implements a color similarity constraint technique based on a radial basis function (RBF) technique to generate a color-constrained mask, and a locality constraint component implements a locality constraint technique based on a fast flood fill technique to generate a locality-constrained mask. The final mask (or matte) output may be an element multiply of the masks generated by the two components.

Abstract: An image processing method is adapted for hue adjustment of an original image pixel. The original image pixel is composed of a plurality of pixel components each having a component value. The image processing method includes: determining a hue zone to which the original image pixel belongs based directly on the component values of the pixel components thereof; obtaining a shifted hue zone according to a predefined hue shift amount, the determined hue zone, and the component values of the pixel components of the original image pixel; and obtaining a hue shifted pixel according to the obtained shifted hue zone, and the component values of the pixel components of the original image pixel.

Abstract: An image processing method of picking up an image of a substrate and converting pixel values of the picked-up substrate image makes the pixel values of the picked-up substrate image into a histogram, and creates a tone curve T composed of a periodic function of a predetermined amplitude and a predetermined period based on a distribution of the pixel values in the histogram. The pixel values of the picked-up substrate image are converted using the tone curve T to obtain a substrate image with a high contrast.

Abstract: An image processing apparatus includes a first attribute image generation unit; a second attribute image generation unit; and a foreground image generation unit. The first attribute image generation unit is configured to determine a first attribute value from an input image to generate a first attribute image. The second attribute image generation unit is configured to determine a second attribute value from the input image to generate a second attribute image. The foreground image generation unit is configured to generate a foreground image expressing color information in the specific region according to the input image, the first attribute image, and the second attribute image. Further, the foreground image generation unit is configured to switch a method of determining a pixel value of a target pixel of the foreground image according to contents of the first attribute image and the second attribute image in a reference region.

Abstract: An edge graph in which a pixel of an image is set as a node and an edge is set between nodes is generated. The dissimilarity or similarity between nodes at the two ends of the edge is used as the feature amount of the edge, and the edge is classified into one of a plurality of classes based on the feature amount. The edge of interest is selected in ascending class order of the feature amount, and it is determined whether to merge determination target regions to which the nodes at the two ends of the edge of interest belong. Determination target regions determined to be able to be merged are merged, and a feature amount in the merged region is updated.

Abstract: A method for detecting and removing scrolling texts comprising a step of using an adaptive transient difference processing of video communication to conduct frame calculation, wherein the adaptive transient difference processing takes first N frames fjkt?N and a current frame fjkt, and subtracts them to obtain a frame difference; and if the frame difference is greater than a threshold value, it is determined that the current frame fjkt has scrolling texts; and interpolates the first N frames before the current position of the scrolling texts to replace the current frame fjkt to achieve the goal of hiding the scrolling texts during video communication to enhance the viewing effect.

Abstract: Methods and apparatus for archival storage of an image are disclosed. The image may be separated into a plurality of bit plane images. The plurality of bit plane images may be written separately onto digital optical tape.

Abstract: Disclosed are a device, a method, and a system for enhancing color. The device comprises a unit used to extract a foreground portion from a whiteboard color image to serve as whiteboard contents; a unit used to stretch R, G, and B channel values of each of a plurality of foreground pixels forming the whiteboard contents; a unit used to adjust color tone of each of the foreground pixels; a unit used to adjust a ratio of color saturation degree to color intensity of each of the foreground pixels so as to cause the ratio to approach a ratio expectation value; and a unit used to increase the color saturation degree and the color intensity of each of the foreground pixel so as to cause the two to approach a color saturation degree expectation value and a color intensity expectation value Id, respectively.

Abstract: Systems and methods of detecting and correcting redeye in an image are described. In one aspect, pixels of the input image are segmented based on projections of color values of the pixels onto two-dimensional thresholding planes. Candidate redeye pixel areas are identified in the input image based on the segmented pixels of the input image.

Abstract: A system and method for detecting human skin tone in one or more images. The system includes an image processing module configured to receive an image and provide contrast enhancement of the image so as to compensate for background illumination in the image. The image processing module is further configured to detect and identify regions of the contrast-enhanced image containing human skin tone based, at least in part, on the utilization of multiple color spaces and adaptively generated thresholds for each color space. A system and method consistent with the present disclosure is configure to provide accurate detection of human skin tone while accounting for variations in skin appearance due to a variety of factors, including background illumination and objects.

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: A computing device is described herein that is configured to select a pixel pair including a foreground pixel of an image and a background pixel of the image from a global set of pixels based at least on spatial distances from an unknown pixel and color distances from the unknown pixel. The computing device is further configured to determine an opacity measure for the unknown pixel based at least on the selected pixel pair.