Abstract: In a method of programming for image enhancement, a content addressable memory is accessed. At least one template is transferred into the content addressable memory. A random access memory is accessed. Enhancement data is transferred into the random access memory. Video data input is inputted into the content addressable memory. Enhancement data is outputted from the random access memory based on the video data matching at least one template.

Abstract: A ridge flow based fingerprint image quality determination can be achieved independent of image resolution, can be processed in real-time and includes segmentation, such as fingertip segmentation, therefore providing image quality assessment for individual fingertips within a four finger flat, dual thumb, or whole hand image. A fingerprint quality module receives from one or more scan devices ridge-flow—containing imagery which can then be assessed for one or more of quality, handedness, historical information analysis and the assignment of bounding boxes.

Abstract: An image processing method is disclosed for processing a first and a second image area of a video frame or a video field. The image processing method includes performing a first operation on the first image area wherein the first operation corresponds to a first criterion, performing a first image processing procedure on the first image area according to the result of the first operation so as to update the first image area, performing a second operation on the second image area wherein the second operation corresponds to a second criterion, and performing a second image processing procedure on the second image area according to the result of the second operation so as to update the second image area.

Abstract: A method and a device are disclosed for segmenting at least one substance in an x-ray image. In at least one embodiment of the method, two attenuation values relating to different energies of an x-radiation are acquired in relation to each pixel. The pixels are mapped into a two-dimensional feature space on the basis of the acquired attenuation values, and there is subsequently determined as assessment variable from the mapping of an image environment respectively assigned to the pixels the number of those pixels that fall in a classification region assigned to the substance. It is then possible to calculate in a simple way on the basis of the assessment variable a segmented image that contains the substance and in which misclassification can largely be avoided by taking account of the neighborhood relationship of the pixels.

Abstract: An 2-D symbol orientation guide with parallel and spaced right angle guidelines with chevron-like spaces provided therebetween is selectively displayed in plural selected dispositions on a monitor screen as an overlay for the display on the same monitor screen of a 2-D Data Matrix symbol. Manual rotation of the symbol is viewed on the monitor screen as the symbols solid line border is moved into alignment with a guide line at which time the symbol is imaged and its quality graded. Display of the orientation guide in at least five selected rotational dispositions, alignment of the symbol solid line border therewith and imaging and grading of the symbol quality in each such position provides multiple grade scores for averaging into an overall grade score.

Abstract: A method for imaging, including counting quanta of energy emitted into a range of angles from particles of an energy emitter distributed over a volume in a body, thereby generating a set of counts. The method further includes defining a probability distribution expression that specifies a local concentration of the particles of the energy emitter over the volume as a function of the set of counts, the function being defined in terms of respective coefficients of a plurality of different scales of the local concentration, including at least a first and a second scale. A dependence of the coefficients of the first scale on the coefficients of the second scale is specified, and the local concentration over the volume is computed by applying the probability distribution expression to the set of counts subject to the specified dependence.

Abstract: A system for creating and viewing customized multimedia segments allows a user to create event identification data from in-band data in a program stream. The in-band data is processed and compiled into event identification data associated with the content stream. The event identification data identifies patterns or sequences of in-band data associated with events in the content stream. Metadata are also included in the event identification data. The event identification data is provided to multimedia devices which receive multimedia content streams containing content streams with in-band data. The in-band data are parsed and compared to the event identification data. If a match occurs, the multimedia device uses the metadata to identify events or perform specified actions.

Abstract: A method and system reconstructs a contone image from a binary image by first tagging pixels to identify one of a multiplicity of image content types. The tag information and the pattern of bits surrounding the pixel to be converted to a contone value are used to reconstruct a contone image from a binary image. The pattern of bits in the neighborhood is used to generate a unique identifier. The unique identifier is used as the address for a lookup table with the contone value to be used. A filter also generates a contone value. A selector selects between the look-up table contone value and the filter contone value based an image context type.

Abstract: A method and apparatus for determining missing color pixel values in image data. Pixel values are interpolated in a horizontal or a vertical direction based on gradient scores and optionally chroma and local statistical scores. Several techniques for refining the interpolation direction determination are also disclosed, including applying a low-pass filter, applying one or more digital filters, and growing an interpolation direction region to nearby pixels. A technique for interpolating corner pixel values is also disclosed.

Abstract: Disclosed herein is a method for detecting thin lines in image data. The method is performed by a processor to process contone image data. The processing includes thresholding a window of pixels using a first set of thresholds established in the contone domain, and then counting and thresholding the binary pixels using a second set of thresholds. The processing in the contone and binary domain are used to determine if a thin line exists and if a pixel of interest in the window is an edge pixel that is part of a thin line. The disclosed method produces better quality output images and reduces the addition of false lines in an image.

Abstract: Disclosed herein is a method for detecting thin lines in image data. The method is performed by a processor to process contone image data. The processing includes combining a first result of thin line detection using a first method and a second result of thin line detection using a second method to produce an improved thin line determination in the image data. The methods include processing and thresholding in the contone and binary domain to determine if a thin line exists in the window of image data. The thin line determination may also be merged with the image data as processed using other image segmentation techniques. The disclosed method produces better quality output images and reduces the addition of false lines in an image.

Abstract: In order to start a frequency analysis process before completion of acquisition of an image so as to shorten a processing time, a first frequency analysis unit performs one-dimensional frequency analysis on each pixel line. A second frequency analysis unit collects a predetermined number of one-dimensional frequency analysis results from the first frequency analysis unit and performs further one-dimensional frequency analysis so as to obtain a final two-dimensional frequency analysis result.

Abstract: A computer implemented method filters input data with a kernel filter. A kernel filter is defined, and a set of unique filter coefficients for the kernel filter are determined. A linkage set is constructed for each unique filter coefficient such that the linkage set includes relative links to positions in the kernel filter that have identical filter coefficients, and in which each relative link is an inverse of the position of the unique filter coefficient. Each input data point is processed by multiply values on which the kernel filter is centered by each of the unique filter coefficients, and adding results of the multiplying to the corresponding output data points as referenced by the relative links.

Abstract: A method filters pixels in a sequence of images. Each image in the sequence is partitioned into blocks of pixels, and the images are processed sequentially. The energy is determined for each block of pixels in each image. The energy of each block is based on variances of intensities of the pixels in the sequence of images. A 3D fuzzy filter is applied to each current pixel in each current block during the sequential processing. The 3D fuzzy filter considers the energy of the block, and the intensities of pixels spatially adjacent and temporally adjacent to the current pixel to remove blocking and ringing artifacts.

Abstract: A method for removing a stationary noise pattern from digital images uses an adaptive noise estimation algorithm to calculate a prediction of the fixed pattern noise and a confidence estimate for the prediction. In one embodiment, a predicted noise value is obtained from the captured image and a predicted image derived from spatial and temporal pixel value prediction techniques. The predicted noise value is used to update a fixed pattern noise estimate only when the confidence estimate for the predicted image is high. In another embodiment, the confidence estimate is used as a weight factor for blending the noise prediction into the noise estimate. In yet another embodiment, the adaptive noise estimation algorithm is applied to a prediction area in the image for calculating scaling parameters which scaling parameters are used to calculate a noise estimate for the entire image based on a reference noise image.

Abstract: Assigning a tag to an object is disclosed. Assigning includes displaying a set of one or more objects, wherein each object has been detected from an image, receiving an indication to tag an object in the set, and assigning a tag to the object.

Abstract: A method is disclosed for enhancing a CT image composed of a plurality of elements, each having an intensity value indicative of a tissue type. The method comprises receiving (101) a first CT image, providing, by enhancement processing (103) based on said first CT image, a plurality of copies of said first CT image, and combining (104) said copies with said first CT image, whereby an enhanced CT image is provided. The combining is based on a classification with respect to intensity values of regions within said first and said copies of said first CT image. The enhancement processing (103) is performed with respect to predetermined intensity value ranges. The method may be implemented as a computer program product or as a device.

Abstract: Methods and apparatus, including computer program products, for filtering an image. A filter kernel is received to determine one or more filtered values for each pixel in a sequence of pixels, where adjacent pixels are separated by a characteristic distance in the image. A difference kernel is defined based on local differences between a first kernel and a second kernel that are defined by the filter kernel centered at a first location and a second location, respectively. The second location is separated from the first location by the characteristic distance separating adjacent pixels in the sequence. The difference kernel is used to determine a difference between filtered values of adjacent pixels in the sequence. For depth of field filtering, the filter kernel can include a blur filter kernel that is based upon depth values of pixels in the sequence.

Abstract: A method and system is provided for reducing mosquito noise in a digital image. The method and system receives an input luminance value for a first pixel in the digital image, and determines whether the first pixel is in relative close proximity to an object appearing in the digital image, based on a comparison of the variation between the input luminance value for the first pixel and luminance values of a first plurality of neighboring pixels. If the first pixel is in relative close proximity to an object, the method performs an average filtering of the input luminance value for the first pixel, based on the luminance values of a second plurality of neighboring pixels, to provide a filtered luminance value for the first pixel.

Abstract: Filtering processing is performed with a difference filter and on two pixels in an image, which pixels are adjacent to each other, and a difference between pixel values of the two pixels, which are adjacent to each other, is thus obtained. A judgment is made as to whether an absolute value of the thus obtained difference is or is not equal to at least a predetermined threshold value. In cases where the absolute value of the difference has been judged to be equal to at least the predetermined threshold value, it is judged that an edge is located between the two pixels, which are adjacent to each other. Detection as to whether an edge is or is not located between the pixels in the image is thus capable of being made quickly with simple operation processing.

Abstract: A thinned output image is generated from an input image. Values of pixels surrounding a pixel of interest in the input image are determined, and first and second neighboring pixel patterns surrounding the pixel of interest are established based on the values of the pixels surrounding the pixel of interest. The first neighboring pixel pattern may be compared to each of a set of purge patterns to determine whether to eliminate the pixel, and the second neighboring pixel pattern may be compared to each of a set of conservation patterns to determine whether to conserve the pixel. The comparisons to the purge and conservation patterns are performed for each pixel independently, and in parallel for all pixels of the input image.

Abstract: A face recognition apparatus and method using Principal Component Analysis (PCA) learning per subgroup, the face recognition apparatus includes: a learning unit which performs Principal Component Analysis (PCA) learning on each of a plurality of subgroups constituting a training data set, and then performs Linear Discriminant Analysis (LDA) learning on the training data set, thereby generating a PCA-based LDA (PCLDA) basis vector set of each subgroup; a feature vector extraction unit which projects a PCLDA basis vector set of each subgroup to an input image and extracts a feature vector set of the input image with respect to each subgroup; a feature vector storing unit which projects a PCLDA basis vector set of each subgroup to each of a plurality of face images to be registered, thereby generating a feature vector set of each registered image with respect to each subgroup, and storing the feature vector set in a database; and a similarity calculation unit which calculates a similarity between the input image

Abstract: Systems and methods are disclosed for applying sketch effects to digital images. An exemplary method may comprise comparing an original image to a filtered image. The method may also comprise rendering changes in the filtered image as lines. The method may also comprise applying connected component labeling to lines in the filtered image to reduce noise. The method may also comprise rendering the filtered image with a sketch effect after reducing noise in the filtered image.

Abstract: Plural window elements are set in one edge window, and edge detection is performed every each the window element, and calculation and determination about its result are made inside an image processing apparatus. A user can freely set a width of the window element and a distance between the adjacent window elements.

Abstract: A printing apparatus comprises a processor comprising registers, and a memory configured to store image data. The processor is configured to load portions of the image data into the registers and perform toner explosion compensation on the portions of the image data loaded in the registers, excluding image data loaded in boundary positions in the registers.

Abstract: A camera includes an image capture unit which captures the image of a subject to obtain image data, a pixel interpolation unit which, on the basis of pixel data from multiple pixels arranged on a line in the image data obtained by the image capture unit, creates image data in an interpolation position on the line, and a storage unit which is stored with common coefficient data for pixel data from multiple pixels which are n-th pixels counted from the interpolation position in opposite directions on the line, the pixel interpolation unit performing interpolation operations on the pixel data from the n-th pixels using the coefficient data stored in the storage unit to thereby create the image data in the interpolation position.

Abstract: Methods and apparatus are provided for electronically trapping a selected digital color image pixel. A plurality of pixels that surround the selected pixel are identified, a colorant value of each of the surrounding pixels is compared with a corresponding colorant value of the selected pixel, one of the surrounding pixels is identified to control trapping of the selected pixel, and the selected pixel is trapped based on a relationship between a colorant value of the selected pixel and a corresponding colorant value of the identified controlling pixel.

Abstract: A color conversion apparatus receives red-green-blue color data, calculates characteristic information and first hue region data from the color data, adjusts the first hue region data according to the characteristic information to obtain second to N-th hue region data, N being an integer equal to or greater than three, generates matrix coefficients for the second to N-th hue region data, and performs a matrix operation on the second to N-th hue region data to obtain color data with four or more color components. Color data with three primary components are thereby converted to color data with four or more primary components by simple calculations, without using a large amount of memory space.

Abstract: A method and apparatus for processing a line pattern using a convolution kernel. An apparatus for processing a line pattern, the apparatus including a light source module radiating predetermined light and a camera module capturing an image of an object, onto which the light is radiated, the apparatus processing a line pattern included in the captured image, includes: a kernel learning unit determining a kernel shape and an optimal threshold value with respect to each vertical interval of the image using a simple line pattern formed at a predetermined location; a convolution application unit applying convolution to a captured test image using the determined kernel shape and optimal threshold value; and a region selection unit scanning each pixel column in the image, to which the convolution is applied, in a vertical direction, and setting pixel values of pixel groups other than a selected pixel group to 0 when a plurality of pixel groups having pixel values other than 0 exists.

Abstract: A duplicate image detection system generates an image table that maps hash codes of images to their corresponding images. The image table may group images according to their group identifiers generated from the most significant elements of the hash codes based on significance of the elements in representing an image. The image table thus segregates images by their group identifiers. To detect a duplicate image of a target image, the detection system generates a target hash code for the target image. The detection system then identifies the group of the target image based on the group identifier of the target hash code. After identifying the group identifier, the detection system searches the corresponding group table to identify hash codes that have values that are similar to the target hash code. The detection system then selects the images associated with those similar hash codes as being duplicates of the target image.

Abstract: Locating an eye includes generating an intensity response map by applying a 3-rectangle filter and applying K-mean clustering to the map to determine the eye. Locating an eye corner includes applying logarithm transform and grayscale stretching to generate a grayscale eye patch, generating a binary map of the patch by using a threshold based on a histogram of the patch, and estimating the eye corner by averaging coordinates weighted by minimal eigenvalues of spatial gradient matrices in a search region based on the binary map. Locating a mouth corner includes generating another intensity response map and generating another binary map using another threshold based on another histogram of the intensity response map. Locating a chin or a cheek includes applying angle constrained gradient analysis to reject locations that cannot be the chin or cheek. Locating a cheek further includes removing falsely detected cheeks by parabola fitting curves through the cheeks.

Abstract: A method of detecting lines in an image comprises using one or more masks for detecting lines in one or more directions out of horizontal, vertical, left diagonal and right diagonal, and further comprises one or more additional masks for detecting lines in one or more additional directions.

Abstract: The pattern defect inspection apparatus is operable to detect defects by comparing a detection image, which is obtained through scanning by an image sensor those patterns that have the identical shape and are continuously disposed on the object under tested at equal intervals in row and column directions, with a reference image obtained by scanning neighboring identical shape patterns in the row and column directions. This apparatus has a unit for generating an average reference image by statistical computation processing from the images of identical shape patterns lying next to the detection image including at least eight nearest chips on the up-and-down and right-and-left sides and at diagonal positions with the detection image being intermediately situated. The apparatus also includes a unit that detects a defect by comparing the detection image to the average reference image thus generated.

Abstract: One embodiment of the present invention relates to a system for reconstructing an image. During operation, the system receives an original image, wherein the original image includes a defective area to be reconstructed. The system also receives a reference to a texture image, which contains a texture to be used during the reconstruction. The system then divides the values of pixels in the defective area and surrounding boundary pixels, by the values of corresponding pixels in the texture image to produce a first intermediate image. Next, the system solves a partial differential equation (PDE) for non-boundary pixels in the first intermediate image subject to values of the boundary pixels in the first intermediate image to produce a second intermediate image. The system then multiplies the values of pixels in the second intermediate image by the values of corresponding pixels in the texture image to produce a replacement image.

Abstract: An 2-D symbol orientation guide with parallel and spaced right angle guidelines with chevron-like spaces provided therebetween is selectively displayed in plural selected dispositions on a monitor screen as an overlay for the display on the same monitor screen of a 2-D Data Matrix symbol. Manual rotation of the symbol is viewed on the monitor screen as the symbols solid line border is moved into alignment with a guide line at which time the symbol is imaged and its quality graded. Display of the orientation guide in at least five selected rotational dispositions, alignment of the symbol solid line border therewith and imaging and grading of the symbol quality in each such position provides multiple grade scores for averaging into an overall grade score.

Abstract: A method and system is provided for processing scanned data representative of a document image for classifying portions of the data into contone, low frequency halftone or high frequency halftone regions. The method comprises identifying an image data value of an original pixel within a portion of a document image. Average pixel values are calculated for the plurality of image regions. First and second halftone noise energy values are computed relative to the original pixel value for the plurality of image regions. The noise values are compared against preselected standards and based upon the comparing, the region can be classified as high frequency halftone, low frequency halftone or contone. Portions of image of data which may introduce unwanted biases in the measurements such as edge portions, all black or all white portions are excluded from the energy level calculations.

Abstract: A method for image processing includes generating a pixel window of image data and determining whether the pixel window-is stable or unstable. Image enhancement values are then obtained from a look up table for stable windows when the window is stable, and image enhancement values are obtained from a look up table for unstable windows when the window is unstable. An enhanced target pixel value is then output according to the obtained look up table image enhancement value.

Abstract: An image processing apparatus comprises a characteristic value generator for receiving image data, analyzing neighboring pixels of a to-be-processed pixel and calculating characteristic values comprising average illumination, illumination variability and histogram of illumination of a local image; a weighting generator for generating first and second weightings according to the characteristic values, wherein the first weighting is inversely proportional to the average illumination and directly proportional to the illumination variability, and the second weighting is relative to the histogram of illumination and illumination of the to-be-processed pixel; a first/second modulated illumination generator for generating first/second modulated illumination according to the illumination of the to-be-processed pixel; and a computation unit for generating first and second weighting illumination according to the first and second weightings and the first and second modulated illumination, and synthesizing the first and

Abstract: An image signal generated by a CCD image sensor is processed by the block-generating section 28 provided in an image-signal processing section 25. A class tap and a prediction tap are thereby extracted. The class tap is output to an ADRC process section 29, and the prediction tap is output to an adaptation process section 31. The ADRC process section 29 performs an ADRC process on the input image signal, generating characteristic data. A classification process section 30 generates a class code corresponding to the characteristic data thus generated and supplies the same to an adaptation process section 31. The adaptation process section 31 reads, from a coefficient memory 32, the set of prediction coefficients which corresponds to the class code. The set of prediction coefficients and the prediction tap are applied, thereby generating all color signals, i.e., R, G and B signals, at the positions of the pixels which are to be processed.

Abstract: A method reduces artifacts in an input image. A variance image is generated from the input image. The input image is partitioned into a plurality of blocks of pixels. A set of classifications is defined. The set of classifications includes smooth, texture, and edge. A particular classification is assigned to each block of pixels of the input image according to the variance image, to generate smooth blocks, texture blocks, and edge blocks. A fuzzy filter is applied to each pixel of only each edge block.

Abstract: [PROBLEMS] To provide a feature extracting method for quickly extracting a feature while preventing lowering of the identification performance of the kernel judgment analysis, a feature extracting system, and a feature extracting program. [MEANS FOR SOLVING PROBLEMS] Judgment feature extracting device (104) computes an interclass covariance matrix SB and an intraclass covariance matrix SW about a learning face image prepared in advance, determines optimum vectors ?, ? which maximizes the ratio of the interclass covariance to the intraclass covariance, derives a conversion formula for converting an inputted frequency feature vector x into a frequency feature vector y in a judgment space, and extracts judgment features of a face image for record and a face image for check by using a restructured conversion formula. Similarity computing device (105) computes the similarity by comparing the judgment features.

Abstract: An 2-D symbol orientation guide with parallel and spaced right angle guidelines with chevron-like spaces provided therebetween is selectively displayed in plural selected dispositions on a monitor screen as an overlay for the display on the same monitor screen of a 2-D Data Matrix symbol. Manual rotation of the symbol is viewed on the monitor screen as the symbols solid line border is moved into alignment with a guide line at which time the symbol is imaged and its quality graded. Display of the orientation guide in at least five selected rotational dispositions, alignment of the symbol solid line border therewith and imaging and grading of the symbol quality in each such position provides multiple grade scores for averaging into an overall grade score.

Abstract: A three-dimensional data controller controls voxel data by distributing the voxel data to hierarchical nodes. The three-dimensional data controller stores combination patterns, each representing combinations of model statuses of lower nodes towards an upper node of the hierarchical nodes, and converts, based on the combination patterns stored, the voxel data into voxel-pattern-data.

Abstract: A method of adaptive pixel correction of a multi-color matrix from a sensor includes collecting pixel values, generating plural vectors, normalizing values and determining an estimated value. The collecting pixel values collects values of a two-dimensional multi-pixel kernel around a particular pixel from the multi-color matrix. The generating plural vectors generates vectors from the kernel where each vector has the particular pixel as a central element. The normalizing values normalizes values for nearest neighbor elements to the central element for each vector. The determining an estimated value determines the value based on the normalized values.

Abstract: In an apparatus which detects a specified pattern, a binarizing unit converts input image data to bi-level image data, and a storage device stores the converted bi-level image data. A pattern detection unit comprises a plurality of detectors which detect a specified pattern (for example, a circular pattern) independently of each other and in parallel to each other. Each of the detectors detects the specified pattern on a block different from those for the other detectors in the bi-level image data stored in the storage device. Then, one most probable block is selected among the blocks including the specified pattern, and careful image recognition is performed on the selected block.

Abstract: With the present invention, data continuity is used at the time of converting an input image into high-quality image data with higher quality than the input image data, to obtain processing results which are more accurate and have higher precision. A class tap extracting unit (902) and prediction tap extracting unit (906) extract a class tap and prediction tap based on data continuity of multiple perimeter pixels corresponding to a pixel of interest in the input image, detected by a data continuity detecting unit (901).

Abstract: Described is a system and method including a user interface to manage sets of digital data (e.g., files) such as digital photographs or email messages. The system and method comprise a rapid sort mechanism and an underlying support mechanism that associates metadata with each set of digital data, including annotation metadata obtained from the sort mechanism. As the user scrolls through images that represent the sets of digital data and categorizes them, metadata as to its particular categorization or lack of categorization is implicitly obtained and associated with each set of digital data. Grouping of sets of digital data into clusters is also provided, with a visual indication as to which cluster a set of digital data belongs. With respect to digital photography, the system and method makes annotating and classifying digital photographs significantly easier and faster than contemporary photograph management mechanisms.

Abstract: A method of comparing an input pattern with a memory pattern includes the steps of loading a representation of said input pattern into cells in an input layer; loading a representation of said memory pattern into cells in a memory layer; loading an initial value into cells in an intermediate layers between said input layer and said memory layer; comparing values of cells in said intermediate layers with values stored in cells of adjacent layers; updating values stored in cells in said intermediate layers based on said step of comparing; and mapping cells in said memory layer to cells in said input layer.

Abstract: A method filters pixels in an image, by first partitioning the image into blocks. Edge block are identified. A variance of an intensity for each pixel in each edge block is determined. Then, each pixel in each edge block is filtered with a filter that is dependant on the variance of the pixel.

Abstract: A method is presented for processing an image of a two-dimensional (2D) matrix symbol having a plurality of data modules and a discontinuous finder pattern, each distorted by “donut effects”. A resulting processed image contains an image of the 2D matrix symbol having a continuous finder pattern suitable for conventional 2D matrix symbol locating techniques, and having a plurality of data modules, each data module having a center more truly representative of intended data, and suitable for conventional 2D matrix symbol sampling and decoding. The method includes sharpening the distorted image of the 2D matrix symbol to increase a difference between low frequency and high frequency image feature magnitudes, thereby providing a sharpened image, and smoothing the sharpened image using a moving window over the sharpened image so as to provide a smoothed image, the moving window and a module of the 2D matrix code being of substantially similar size.