Abstract: A picture quality controlling device (10) that controls a picture quality for an image signal which is input including: a histogram generation unit (14) generating a histogram for at least one of brightness, chromaticity, color, and frequency information pieces from an image contained in the image signal; a threshold value comparing unit (17) comparing the histogram with a threshold value previously set for the histogram in order to determine whether control of the picture quality for the image signal is necessary; and a picture quality controlling unit (18) extracting a histogram pattern corresponding to the histogram from a reference table including plural predetermined histogram patterns, and controlling the picture quality based on a controlled parameter corresponding to the extracted histogram pattern if the control is determined to be necessary based on a result obtained by the threshold value comparing unit.

Abstract: A white balance method for a display image is disclosed. The steps of the method includes: measuring gray levels of a basic and reference colors based on a plurality of color temperatures; obtaining reference color gains according to average values of the gray level of the reference and basic colors and a ratio according to the reference color gains corresponding to each of the color temperatures; dividing the display image into a plurality of blocks, and obtaining a reference color gain of each of blocks according to the average values of the gray levels of reference and basic colors, and obtaining a block ratio of each of blocks; generating a selected number corresponding to each of the color temperature according to the ratios and the block ratios; selecting the basic and reference color gains of one of the color temperatures for executing white balance to the display image.

Abstract: A signal processor which performs gradation conversion processing using a histogram of an image signal is provided with a feature calculating unit which calculates a feature of the image signal; an interval setting control unit which sets intervals of a pixel value in the histogram when a histogram of the image signal is obtained, according to the calculated feature, so as to obtain the histogram of the local region of the image signal; a gradation-conversion-characteristic calculating unit which calculates a gradation conversion characteristic, using the histogram obtained by using the intervals set at the interval setting control unit; and a gradation converting unit which performs gradation conversion to the image signal using the gradation conversion characteristic.

Abstract: A technique for estimating background motion in monocular video sequences is described herein. The technique is based on occlusion information contained in video sequences. Two algorithms are described for estimating background motion: one fits well for general cases, and the other fits well for a case when available memory is very limited. The significance of the technique includes: a motion segmentation algorithm with adaptive and temporally stable estimate of the number of objects is developed, two algorithms are developed to infer occlusion relations among segmented objects using the detected occlusions and background motion estimation from the inferred occlusion relations.

Abstract: The present invention is directed to an apparatus and method for the processing of a mixed color document. The mixed color document is preferably a digital structured document containing metadata, such as e.g. a PDF document. The mixed color document is split into at least a first part to be processed in a first processing channel and into at least a second part to be processed in a second, color-dedicated, processing channel. In executing the splitting judgement, color functionality rather than bare color content is taken into account.

Abstract: Systems and methods for segmenting images comprising cells, wherein the images comprise a plurality of pixels; one or more three dimensional (3D) clusters of cells are identified in the images; and the 3D clusters of cells are automatically segmented into individual cells using one or more models.

Abstract: A method and apparatus is disclosed herein for image processing. In one embodiment, the method comprises performing an analysis corresponding to a sequence of drawing commands that create a bit-map when executed and generating a set of image segments based on the analysis corresponding to the sequence of drawing commands.

Abstract: The object of this invention is to provide an image processing apparatus in which, in processing of a document image read by a document reading device, an inclination of a character string in the document image which is recognized in character recognition is obtained more accurately. The image processing apparatus includes a similar character extraction portion which extracts and outputs a character group comprised of characters having a shape and a size that are same with or similar to each other from among characters constituting a character string comprised of a character recognized in optical character recognition from a document image read by a document reading device; and an inclination calculation portion which calculates an inclination value of the character string based on position information of each character of the character group output from the similar character extraction portion.

Abstract: A method for filtering a digital image, comprising segmenting the digital image into a plurality of tiles; computing tile histograms corresponding to each of the plurality of tiles; deriving a plurality of tile transfer functions from the tile histograms preferably using 1D convolutions; interpolating a tile transfer function from the plurality of tile transfer functions; and filtering the digital image with the interpolated tile transfer function. Many filters otherwise difficult to conceive or to implement are possible with this method, including an edge-preserving smoothing filter, HDR tone mapping, edge invariant gradient or entropy detection, image upsampling, and mapping coarse data to fine data.

Abstract: An image processing apparatus of the present invention includes: a blank document determination section determining whether or not input image data is image data of a blank document, regardless of a process mode set for setting a process with respect to the input image data; a storage device storing the input image data in association with a determination result made by the blank document determination section; and a control section (i) reading out the input image data from the storage device and (ii) excluding the input image data determined as image data of a blank document by the blank document determination section, from images to be displayed by the image display device, when the image display device carries out a preview display of the input image data. This configuration makes it possible to carry out a preview display in which a blank document (blank page document) is skipped, without reading the document again.

Abstract: A set of pixels of a background element is identified according to a mask that defines a shape of a foreground element. A color value for a pixel of the foreground element is determined. The determining includes ascertaining a value of a measure of brightness of one or more pixels of a set of pixels of the background element and calculating the color value for the pixel of the foreground element based on the value of the measure of brightness and a value of an adjustable contrast variable. The calculating the color value for the pixel of the foreground element preserves in the foreground element a color component of the one or more pixels of the set of pixels of the background element and increases contrast with the value of the measure of brightness according to the value of the adjustable contrast variable.

Abstract: Three-dimensional (3D) glasses, a method for driving 3D glasses, and a system for providing a 3D image are provided. The 3D glasses driving method includes detecting a first pattern corresponding to a left eye image and a second pattern corresponding to a right eye image from a 3D display apparatus, converting the first pattern into a first histogram and the second pattern into a second histogram, comparing the converted first and second histograms with first and second optimal histograms, and adjusting an opening or a closing of a left eye glasses part and a right eye glasses part of the 3D glasses based on the comparison.

Abstract: Methods and computer program products for quantitative three-dimensional (“3D”) image correction in optical coherence tomography. Using the methods and computer program products, index interface (refracting) surfaces from the raw optical coherence tomography (“OCT”) dataset from an OCT system can be segmented. Normal vectors or partial derivatives of the curvature at a refracting surface can be calculated to obtain a refracted image voxel. A new position of each desired refracted image voxel can be iteratively computed. New refracted corrected voxel positions to an even sampling grid can be interpolated to provide corrected image data. In some embodiments, clinical outputs from the corrected image data can be computed.

Abstract: An image based document index and retrieval method is described. During document indexing, each source document is analyzed to generate index information at document, page, region and unit levels. Region and unit level index information is generated by segmenting each text region into units, constructing unit length or unit density histograms, and analyzing the units in a few most frequent bins of the histogram. The index information and the source document images are stored in a database. During document retrieval, a target document is analyzed to generate target index information in the same way as during document indexing. The target index information is compared to stored index information in a progressive manner (from higher to lower levels) to identify source documents with index information that matches the target index information. Fuzzy logic is used in the comparison steps to increase the robustness of the document retrieval.

Abstract: A method for sharpening a captured image includes the steps of (i) identifying a plurality of edge pixels in the captured image, (ii) reviewing the plurality of edge pixels to identify one or more line pixels, and one or more non-line pixels in the captured image (354), and (iii) sharpening the captured image utilizing a first level of overshoot control for the non-line pixels (362), and utilizing a second level of overshoot control for the line pixels (360) The method also includes the steps of (i) identifying an intensity value for each of a plurality of neighboring pixels that are positioned near a selected pixel in a predetermined pixel window that have the highest intensity values and the lowest intensity values.

Abstract: Provided is a moving image processing apparatus including a cut transition detection unit configured to detect inter-cut transition from a moving image including a plurality of cuts; a cut pair specifying unit configured to specify cut pairs repeated as a series of different cuts based on a feature amount of each cut; and a cut structure image generation unit configured to generate a cut structure image including a representative image of each cut arranged in an order of the cut transition and indicating a boundary between the cut pairs.

Abstract: A method for recognizing markers printed on a learning material, includes sampling an image of the learning material; grouping the sampled image of pixels into a first image group and a second image group based on a threshold; and calculating medians of the first image group and the second image group to update the threshold with a first average value of the calculated medians. Further, the method for recognizing markers printed on the learning material includes repeating the above until a difference between a previous threshold and an updated threshold is equal to or smaller than a reference value; binarizing an image captured by a camera based on the updated threshold; and detecting the markers based on the binary image.

Abstract: A method and an apparatus for bilayer image segmentation are described. A set of segmentation seeds for the image is generated by analyzing a depth histogram of the image. Then a segmentation map is generated by minimizing an objective function, which models a directed flow from the foreground segmentation seeds towards the background segmentation seeds.

Abstract: A method is described for binarizing a gray scale document image, in particular, a document image containing both text and non-text contents. Phase congruency maps are calculated from the gray scale image, and used to segment the text and non-text areas of the gray scale image. The phase congruency maps are also used to extract long lines such as table lines, which can be optionally removed from the image. The text and non-text areas of the gray scale image are divided into image patches; for the text areas, connected components obtained from the phase congruency map are used to generate image patches, so that each image patch contains a text character. The image patches are binarized individually using individual threshold values, and then combined to generate a binary image of the gray scale image. The method can also be used for purposes of OCR or document authentication.

Abstract: One of the challenges in video surveillance system is the detection of unwanted intruders in secure zones. These zones may be in large facilities such as airports, train stations, port facilities or warehouses. Because many of these locations are outdoors, the presence of shadows is detected on images. In order to effectively eliminate these shadows which will therefore result in a usable figure, these shadows must be eliminated. This is accomplished by forming a contour box around the image and then reducing the shadows based on preset parameters in the software.

Abstract: A system and method for modeling a region segmented image is described. Aspects of the present invention may include the generation of a computer model that models the region segmented image, the computer model comprising one or more nodes, wherein each node in the one or more nodes represents an arbitrarily shaped region present in the region segmented image, and each of the arbitrarily shaped regions comprises an image segment wherein the image segment is an indivisible partition in the region segmented image. The model may additionally comprise one or more logical nodes, wherein each logical node represents an image region formed by the union of two or more arbitrarily shaped image regions in the region segmented image that exhibit at least one type of spatial relationship and a hierarchical graph representation of the region segmented image. Types of spatial relationships may include hierarchical, adjacent and cohesive spatial relationships.

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: Display devices and methods for operating a display device are provided. A display device has a source of an original image and a display. A user input system is adapted to generate a non-directional signal in response to a user input action. A controller is provided and is adapted to detect the non-directional signal and to successively designate a different one of a set of portions of the original image in response to each non-directional signal. The controller is further adapted to cause the display to present a portion evaluation image showing the currently designated portion of the original image and to determine and area of importance in the original image based upon the currently designated portion. At least one of the portions of the set of portions of the original image is non-central with respect to the original image.

Abstract: A method performed by a software process executing on a computer system includes selecting a first set of pixels in a digital image in the RGB color space. The pixels are selected such that, for each pixel in the set, a red component is a highest value component and a blue component is a lowest value component. The method also includes identifying at least a subset of the first set as a region of orange hue in the digital image.

Abstract: A system including a processor for adjusting the dynamic range of an image including a plurality of pixels. The processor segments the pixels into blocks, and computes statistical values for each block based on intensity values of the pixels. The processor also adjusts the dynamic range of the image by controlling the intensity values of the pixels based on the statistical values.

Abstract: A method is described for processing an image to generate a signature which is characteristic of a pattern within the image. The method includes: receiving an image; overlaying a window at multiple locations on the image to define a plurality of sub-images within the image, with each sub-image each having a plurality of pixels having a luminance level; determining a luminance value for each sub-image where the luminance value is derived from the luminance levels of the plurality of pixels; and combining the luminance values for each of the sub-images to form the signature. The combining is such that the signature is independent of the location of each sub-image. A method of creating a database of images using the method of generating signatures is also described.

Abstract: A difference in intensities of a pair of pixels in an image is repeatedly compared to a threshold, with the pair of pixels being separated by at least one pixel (“skipped pixel”). When the threshold is found to be exceeded, a selected position of a selected pixel in the pair, and at least one additional position adjacent to the selected position are added to a set of positions. The comparing and adding are performed multiple times to generate multiple such sets, each set identifying a region in the image, e.g. an MSER. Sets of positions, identifying regions whose attributes satisfy a test, are merged to obtain a merged set. Intensities of pixels identified in the merged set are used to generate binary values for the region, followed by classification of the region as text/non-text. Regions classified as text are supplied to an optical character recognition (OCR) system.

Abstract: An electronic device and method use a camera to capture an image of an environment outside followed by identification of regions therein. A subset of the regions is selected, based on attributes of the regions, such as aspect ratio, height, and variance in stroke width. Next, a number of angles that are candidates for use as skew of the image are determined (e.g. one angle is selected for each region. based on peakiness of a histogram of the region, evaluated at different angles). Then, an angle that is most common among these candidates is identified as the angle of skew of the image. The just-described identification of skew angle is performed prior to classification of any region as text or non-text. After skew identification, at least all regions in the subset are rotated by negative of the skew angle, to obtain skew-corrected regions for use in optical character recognition.

Abstract: An attribute is computed based on pixel intensities in an image of the real world, and thereafter used to identify at least one input for processing the image to identify at least a first maximally stable extremal region (MSER) therein. The at least one input is one of (A) a parameter used in MSER processing or (B) a portion of the image to be subject to MSER processing. The attribute may be a variance of pixel intensities, or computed from a histogram of pixel intensities. The attribute may be used with a look-up table, to identify parameter(s) used in MSER processing. The attribute may be a stroke width of a second MSER of a subsampled version of the image. The attribute may be used in checking whether a portion of the image satisfies a predetermined test, and if so including the portion in a region to be subject to MSER processing.

Abstract: A method and system for generating a cartoon are provided. The method includes receiving a digital image for processing at a server. The method includes executing a color structure coding procedure to produce a color-reduced interim image. The method includes generating a sketch from the digital image with a Difference of Gaussian procedure. The method includes combining the color-reduced interim image and the sketch into a processed cartoon.

Abstract: There is provided an apparatus and a method for generating an album while adequately allocating images per page in accordance to image capturing-times. The album creating apparatus has an image storing section for storing images correlating with image capturing-times of the images, a distribution-of-image-capturing-time calculating section for calculating a distribution of image capturing-times of the plurality of images stored in the image storing section based on the image capturing-times of the plurality of images stored in the image storing section, an image sorting section for sorting the plurality of images stored in the image storing section per page in the album based on the distribution of image capturing-times calculated by the distribution-of-image-capturing-time calculating section and a layout determining section for laying out the images sorted by the image sorting section per page to each page of the album.

Abstract: A region extraction apparatus includes an image acquisition device that acquires an image, a temporary initial region specifying device that specifies a plurality of temporary initial regions in the acquired image, a separation calculation device that calculates a separation that is an indicator indicating how much pixel values of all pixels of an inside of a specified temporary initial region and pixel values of all pixels of an outside of the specified temporary region are different from each other, on each temporary initial region, an initial region specifying device that specifies a temporary initial region having a highest calculated separation as an initial region, and a region extraction device that performs a region extraction on a basis of the specified initial region.

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: Systems, methods, and computer readable media to register images in real-time and that are capable of producing reliable registrations even when the number of high frequency image features is small. The disclosed techniques may also provide a quantitative measure of a registration's quality. The latter may be used to inform the user and/or to automatically determine when visual registration techniques may be less accurate than motion sensor-based approaches. When such a case is detected, an image capture device may be automatically switched from visual-based to sensor-based registration. Disclosed techniques quickly determine indicators of an image's overall composition (row and column projections) which may be used to determine the translation of a first image, relative to a second image. The translation so determined may be used to align/register the two images.

Abstract: Provided is a face clustering device that detects a face included in an image, detects a direction of the detected face, detects, taking into account the detected direction of the face, a face with a similar feature and forms a collection of pieces of face information showing a feature of this face, narrows down, for each collection of pieces of face information which has been formed, the number of pieces of face information to a number set in advance for each face direction and sets each collection of pieces of face information for which the number has been narrowed down as a unit group, and performs, with the set unit group as a unit, clustering based on pieces of face information included in each unit group.

Abstract: A target extracting apparatus and method for extracting a target through probability modeling of pixel brightness values in an image, and a recording medium storing a program for performing the method, are disclosed. The method includes extracting a background image from an input image, modeling brightness values of the input image and the background image based on a Gaussian distribution to generate an input image modeling result and a background image modeling result, calculating likelihood ratios for determining whether a pixel in the input image corresponds to a target based on a correlation between the input image modeling result and the background image modeling result and target templates having different sizes; determining a location of the target based on the calculated likelihood ratios; and outputting the determined location of the target.

Abstract: An image taking system including: (a) a CMOS or CCD image sensor; (b) an interest-region setter configured to set regions of interest within an image taking area of the image sensor; (c) an acquiring-condition determiner configured to determine an image-data acquiring condition required for acquiring at least two image data generated in at least two of the regions of interest; and (d) an image-data acquirer configured to acquire the at least two image data. The acquiring-condition determiner includes an exposure-time determining portion configured to determine, as the image-data acquiring conditions, at least two different exposure times required for acquiring the at least two image data generated in the at least two regions of interest. The image-data acquirer includes an exposure-time-based-image-data acquiring portion configured to acquire the at least two image data, such that the acquired at least two image data are based on the at least two different exposure times.

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: Method for detecting edge of fixed pattern includes receiving and analyzing a first image to obtain a first edge information. Second image and a corresponding second edge information are received, in which the second image includes an accumulation of image history information. According to the first edge information and the second edge information, a consistent number and an inconsistent number for pairs of pixels at the corresponding location of the first image and the second image are calculated, in which the consistent number represents how many pairs of pixels of which two compared pixels of each pair are both edge pixels, and the inconsistent number represents one of the two compared pixels is not the edge pixel. When the consistent number is greater than first predetermined value and meanwhile the inconsistent number is less than second predetermined value, first image and second image have a fixed pattern with fixed edge.

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: Plural points present on a boundary surface dividing a subject are set as input points. A plane approximating the boundary surface is determined as a reference plane by using the input points. Plural supplementary points are set on the reference plane on the outside of the subject. A surface approximating the boundary surface is generated by interpolating points between the input points by using the supplementary points and the input points. The subject is divided into separate regions by using the generated surface as a boundary surface.

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 disclosure describes systems, methods, and mediums for adjusting an exposure of a digital image using a histogram. The systems, methods, and mediums may include generating, by a computing device, a histogram associated with plurality of pixels in an image and enabling adjustment of the histogram to generate an adjusted histogram. The systems, methods, and mediums may further include generating, by the computing device, at least one adjusted control setting by adjusting at least one control setting in response to generation of the adjusted histogram and capturing the image in a memory device in response to generating the at least one adjusted control setting.

Abstract: A system and method are disclosed for detecting and labeling places recognized in a video stream using change-points detection. The system includes a segmentation module and a label learning module. The segmentation module is configured to receive a video stream comprising multiple digital representations of images. The video stream is represented by a measurement stream comprising one or more image histograms of the video stream. The segmentation module segments the measurement stream into multiple segments corresponding to place recognized in the videos stream. The segmentation module detects change-points of the measurement stream and computes probability distributions of the segments over multiple pre-learned place models. The label generation module is configured to generate place labels for the places recognized by the place models.

Abstract: A system and a method for identification of alphanumeric characters present in a series in an image are disclosed. The system and method captures the image and further processes it for binarization by computing a pattern of the image. The generated binarized images are then filtered for removing unwanted components. Candidate images are identified out of the filtered binarized images. All the obtained candidate images are combined to generate a final candidate image which is further segmented in order to recognize a valid alphanumeric character present in the series.

Abstract: Disclosed is a method of performing contrast enhancement for an image. A mean luminance value is calculated with respect to an image that is read, the type of the image is determined based on the mean luminance value, a contrast reference curve is created by using a hyperbolic tangential function curve according to the type of the image, and the contrast of the image is enhanced by using the contrast reference curve.

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: A method performed by a software process executing on a computer system, includes obtaining a digital image having a plurality of pixels encoded in a YUV color space. Each pixel has a luma component of value Y, a blue color-difference component of value U and a red color-difference component of value V. For a specified pixel, the method includes calculating whether U is less than a first threshold and V is greater than a second threshold. The method further includes determining whether the specified pixel potentially depicts an orange hue depending on a result of the calculation.

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 are disclosed for detecting and labeling places in a video stream using change-points detection. The system comprises a place label generation module configured to assign place labels probabilistically to places in the video stream based on the measurements of the measurement stream representing the video. For each measurement in the segment, the place label generation module classifies the measurement by computing the probability of the measurement being classified by a learned Gaussian Process classifier. Based on the probabilities generated with respect to all the measurements in the segment, the place label generation module determines the place label for the segment. In cases where a Gaussian Process classifier cannot positively classify a segment, the place label generation module determines whether the segment corresponds to an unknown place based on the perplexity statistics of the classification and a threshold value.