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: A method for providing an output image based on an input image, the method comprising determining a location of an output pixel with respect to an input image, determining values of elements of a filter array such that the effective width of the filter array depends on the density of exposed input pixels within the input image, and determining the value of the output pixel by performing a sum-of-products operation between non-zero values of the elements of the filter array and the values of input pixels of the input image located at respective positions, when the filter array is superimposed on the input image such that the center of the filter array corresponds to the location of the output pixel.

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: An automatic brightness adjusting method and apparatus for image signal processor (ISP) is provided. The image processing apparatus may include a histogram generating unit, a cumulative distribution function calculator, and a histogram equalization (HE) unit. The histogram generating unit may generate a histogram of brightness values of pixels in an input image. The cumulative distribution function calculator may generate a cumulative distribution function and an inverse cumulative distribution function, based on the generated histogram. The HE unit may generate a conversion function based on the cumulative distribution function and the inverse cumulative distribution function, and may apply HE to the input image based on the conversion function so as to generate an output image.

Abstract: The image correction processing device (100) disclosed in the description is configured by integrating a first external terminal (CAMDI) [7:0] to which digital input image data is inputted from outside of the device, an image correction processing circuit (200) applying predetermined image correction processing on the digital input image to create digital output image data, a second external terminal (CAMDO) [7:0] outputting the digital output image data to the outside of the device, an encoder circuit (300) converting the digital output image data to analog composite video-type output image data, and a third external terminal (VOUT) outputting the analog composite video-type data to the outside of the device.

Abstract: Machine vision based obstacle avoidance system is provided. The system utilizes a CCD camera to capture an image. A normalized image and dynamic masking is used in object detection.

Abstract: Techniques to improve image fusing operations using intensity mapping functions (IMFs) are described. In one approach, when a reference image's pixel values are within its' IMF's useful range, they may be used to generate predicted secondary image pixel values. When the reference image's pixel values are not within the IMF's useful range, actual values from a captured secondary image may be used directly or processed further to generate predicted secondary image pixel values. The predicted and actual pixel values may be used to construct predicted secondary images that may be fused. In another approach, the consistency between pixel pairs may be used to generate consistency-based weighting factors that may be used during image fusion operations.

Abstract: A method for evaluating video quality of a video stream comprising the steps of a) calculating, for at least a first frame of a series of frames from said video stream, a true value of at least one video quality-related parameter associated to said first frame; b) calculating a predicted value of said video quality-related parameter for at least a second frame from said series of frames based on said true value associated to said first frame; c) calculating a true value of said video quality-related parameter associated to said second frame; and d) judging the video quality of said second frame based on a difference between true and predicted values of the at least one video quality-related parameter associated to said second frame.

Abstract: Disclosed is a method and a device for denoising a video based on non-local means, which is capable of making self-adaptive adjustment in response to illumination variance of the frame in the video.

Abstract: Techniques are described for improving accuracy and speed of video fingerprinting and identification by using video frame color and intensity information. Multiple approaches for generating a novel signature based on video frame color information are described. One is based on spatial distribution of pixel intensities with reference to derived color groups, while another is based on thresholding a joint histogram of pixel intensity, color, and spatial coordinates. These color based signatures can be deployed either as primary video content signatures, or as hash traversal signatures used to improve speed of an initial stage of video data base search procedures. They can also be used as secondary signatures during a video signature data base search with primary video content signatures, to help disambiguate possible false positive matches, and to improve marginal matches which might not be identified otherwise.

Abstract: Color management which converts source device colors into counterpart colors in a destination device color space. Device independent source and destination device gamut boundaries are obtained. A color image is generated in the source device color space. The color image is transformed into an image in a device independent color space. A gamut boundary for the device independent image is generated, based on the content of the device independent image. The source device gamut boundary is shrunk in a hue symmetric manner, such that color hues do not change, until it touches the image gamut boundary. Colors of the device independent image are mapped onto a gamut of the destination device by invoking a compression-type gamut mapping algorithm that uses the modified source device gamut boundary and the destination device gamut boundary to perform gamut mapping. The gamut mapped colors are converted into colors in destination device dependent color space.

Abstract: Techniques are disclosed relating to automatically adjusting images. In one embodiment, an image may be automatically adjusted based on a regression model trained with a database of raw and adjusted images. In one embodiment, an image may be automatically adjusted based on a model trained by both a database of raw and adjusted images and a small set of images adjusted by a different user. In one embodiment, an image may be automatically adjusted based on a model trained by a database of raw and adjusted images and predicted differences between a user's adjustment to a small set of images and a predicted adjustment based on the database of raw and adjusted images.

Abstract: A pixel processing method includes: selecting a first plurality of color component values of a first plurality of pixels within a pixel block in a buffering device, performing a first color component process upon a first target pixel in the first plurality of pixels to determine a first target color component value of the first target pixel; and selecting a second plurality of color component values of a second plurality of pixels within the pixel block at the same time as the first color component process is performed, and performing a second color component process upon a second target pixel in the second plurality of pixels according to the second plurality of color component values to determine at least one underdetermined target color component value of the second target pixel, wherein the second target pixel has been processed by the first color component process.

Abstract: In accordance with one or more aspects of the image-based backgrounds for images, an image is analyzed in order to identify a color that represents the image. An enhanced background is generated based at least in part on the identified color, and both the image and the enhanced background are output on a screen. In addition, or alternatively, the identified color can be saved as being associated with the image in order to be used to generate an enhanced background for the image when the image is displayed.

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: In a first exemplary embodiment of the present invention, an automated, computerized method is provided for processing an image. According to a feature of the present invention, the method comprises the steps of providing an image file depicting an image defined by image locations, in a computer memory, generating a bi-illuminant chromaticity plane in a log color space for representing the image locations of the image in a log-chromaticity representation for the image, providing a set of estimates for the orientation of the bi-illuminant chromaticity plane and calculating an orientation for each one of the image locations as a function of the set of estimates for the orientation.

Abstract: An image processing apparatus includes a histogram creation unit that creates a histogram from an input image, a detection unit that detects a gradation level of interest from the histogram, a gradation correction parameter generation unit that generates a gradation correction parameter to improve a gradation characteristic in a gradation range around the gradation level of interest, and a correction unit that corrects the gradation of the image using the gradation correction parameter. The detection unit detects, as the gradation level of interest, a gradation level whose frequency is a peak value equal to or more than a predetermined threshold, and which has variation width of frequencies in a predetermined range including this gradation level to be smaller than a predetermined width in the histogram.

Abstract: A method of recognizing a user's dynamic organ for use in an electric-using apparatus includes scanning a difference image, which reflects brightness difference between a target image and a comparative image that are inputted through an imaging element, using a window; generating a HOG (histograms of oriented gradients) descriptor of a region of the difference image that is scanned when it is judged that the scanned region includes a dynamic organ; measuring a resemblance value between the HOG descriptor of the scanned region and a HOG descriptor of a query template for a gesture of the dynamic organ; and judging that the scanned region includes the gesture of the dynamic organ when the resemblance value meets a predetermined condition, wherein the comparative image is one of frame images previous to the target image.

Abstract: A method of recognizing a user's dynamic organ for use in an electric-using apparatus includes scanning a target image inputted through an imaging element using a window; generating a HOG descriptor of a region of the target image that is scanned when it is judged that the scanned region includes a dynamic organ; measuring a resemblance value between the HOG descriptor of the scanned region and a HOG descriptor of a query template for a gesture of the dynamic organ; and judging that the scanned region includes the gesture of the dynamic organ when the resemblance value meets a predetermined condition.

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: The shadows and highlights regions of an image can be automatically optimized in a localized manner. A mask can be generated that can automatically identify local regions of a digital image as highlight regions or shadow regions. Different processing can then be automatically applied to highlight regions separately from the shadow regions. Luminance histograms can be obtained for the overall digital image, as well as those portions of the digital image that are in the highlights regions and, separately, the shadows regions. The moments of those histograms, including the average and the variance, can be compared to target moments and processing can continue to be applied to highlights regions and, separately, shadows regions, until one or more target moments are achieved. Target moments can be generated from original moments of the original image histograms based on relationships generated from a prior manual optimization of a reference set of images.

Abstract: Techniques are disclosed involving contrast adjustment for images. For example, an input image is classified based on its pixel value characteristics, as expressed in an input brightness histogram. From such a classification, a target histogram distribution for a corresponding output image (i.e., a contrast-adjusted transformation of the input image) may be specified. With the target histogram of the output image specified, a transformation function may be derived that maps input image values to output image values. Moreover, transitions of such transformation functions may be smoothed. Such smoothing may provide advantages, such as a reduction in flickering associated with video data.

Abstract: Described is a hierarchical filtered motion field technology such as for use in recognizing actions in videos with crowded backgrounds. Interest points are detected, e.g., as 2D Harris corners with recent motion, e.g. locations with high intensities in a motion history image (MHI). A global spatial motion smoothing filter is applied to the gradients of MHI to eliminate low intensity corners that are likely isolated, unreliable or noisy motions. At each remaining interest point, a local motion field filter is applied to the smoothed gradients by computing a structure proximity between sets of pixels in the local region and the interest point. The motion at a pixel/pixel set is enhanced or weakened based on its structure proximity with the interest point (nearer pixels are enhanced).

Abstract: An auto-focus image system includes a focus signal generator and a pixel array coupled thereto that captures an image that includes a plurality of edges. The generator computes a focus signal from a plurality of edge-sharpness measures, each measured from and contributed by a different edge as a quantity with a unit that is a power of a unit of length. The generator reduces a relative weight of the contribution of an edge depending on a shape of a normalized gradient profile of the edge as identified by an n-tuple of values of n different shape measures (n?2). Each shape measure varies across normalized gradient profiles of different shapes. One shape measure may be the edge-sharpness measure itself. The weight may be zero if the n-tuple falls outside a predetermined region. At least one symmetrical shape that has perfect reflection symmetry receives reduced weight.

Abstract: Techniques for generating a gradient characterization for a first fingerprint image are provided. One or more fingerprint feature points are selected from the first fingerprint image. A region is obtained for each of the one or more selected fingerprint feature points. The region is a representation of an area proximate a given fingerprint feature point. Each of the obtained regions is divided into a plurality of sub-regions. A histogram is generated for each of the plurality of sub-regions. For each of the one or more selected fingerprint feature points, the one or more generated histograms are combined into a concatenated histogram. The concatenated histogram is used for identification purposes.

Abstract: There is provided an image processing device which transforms an image with a bit depth of N into an upper layer with a bit depth of M and a remaining lower layer, including a histogram unit that generates histogram indicating occurrence frequency of each pixel value of an image with a bit depth of N, a table unit that generates a table listing pixel values of which occurrence frequency in the histogram generated by the histogram unit is equal to or more than one, a reordering unit that reorders an arrangement of values in the histogram using the table generated by the table unit, an update unit that updates the table generated by the table unit and the histogram reordered by the reordering unit; and an index image unit that generates an index image with a bit depth of N using the updated table and the updated histogram.

Abstract: A method, medium, and apparatus processing depth information of a depth image. The apparatus adaptively presenting information on depth information includes a section determination unit determining which one of plural sections respective depth values for pixels of the 3D image fall within, with the plural sections being defined by a measured limit distance for the 3D image being parsed into the plural sections based on distance based depth resolution information, and an adaptive quantization unit to selectively quantize and represent each depth value based on a respective predefined quantization setting of the one section.

Abstract: According to an aspect of the invention, an image processing apparatus includes a generating unit, a calculating unit, a receiving unit, and a changing unit. The generating unit generates a plurality of histograms of images with respect to each color based on an input image. The calculating unit calculates a plurality of first image densities of the images from the histograms. The receiving unit receives a content of image quality adjustment performed on the input image. The changing unit changes one of the histograms based on the content of the image quality adjustment. The one of the histogram corresponds to one of the images on which the image quality adjustment is performed. The calculating unit calculates a second image density corresponding to the one the images based on the one of the histogram changed by the changing unit.

Abstract: An apparatus for the detection of a geometrical position of plastics material containers, for example, plastics material pre-forms, having a base member and a thread region may include an image-recording device, which records a locally resolved image of the plastics material container. The image-recording device is arranged in such a way that it observes the plastics material container substantially along its longitudinal direction. The apparatus includes an illumination device, which illuminates at least one region of the plastics material container observed by the image-recording device, and an evaluation device, which on the basis of an image recorded by the image-recording device determines a rotary setting of the plastics material container with respect to its longitudinal direction.

Abstract: Embodiments provide a unified method for combining images such as high dynamic range images, flash-no-flash image pairs, and/or other images. Weight masks are defined for each of the plurality of images by calculating coefficients for each of the weight masks. Calculating the coefficients includes, at least, performing histogram alignment between a reference image and each of the other input images and by applying a mismatch bias to the coefficients as a function of the histogram alignment. After applying the weight masks to the corresponding images, the images are combined to produce a final image.

Abstract: A method for extracting a target from a series of images includes the steps of: (a) estimating an ambient temperature value of pixels in the series of images; (b) finding a band of pixel values having temperature values above the ambient temperature value, the band of pixel values forming a histogram; and (c) differentiating the histogram to estimate a threshold. Also included are steps (d) extracting the target having pixel values above the threshold; and (e) colorizing the target for display.

Abstract: An apparatus for detecting disparity is described.

Abstract: An image converting device includes; a downscaling unit which downscales a two-dimensional image to generate at least one downscaling image, a feature map generating unit which extracts feature information from the downscaling image to generate a feature map, a visual attention calculating unit which generates a low-level attention map based on a visual attention of the feature map, and an image expansion unit which up-scales the low-level attention map, wherein an increasing gray value may be added to image data disposed on the upper portion in the low-level attention map, and 0 or a decreasing gray value may be added to the image data disposed on the lower portion.

Abstract: Image data is divided into blocks and a histogram of a color appearing in a target block is formed. A target color region is decided as significant, if the area of that region is larger than a threshold, or if that area is smaller than the threshold and if that region is located at a boundary of the target block and attribute information for the pixel at the boundary in that region indicates a preset attribute. If that region is not decided as significant, to integrate that region to a region of another color which contacts that region, the color of the pixel in that region is substituted by the other color. If that region is decided as significant and if the chrominance difference between that region and the region decided as significant in another block which contacts the target block is smaller than another threshold, these regions are integrated.

Abstract: Some embodiments provide a novel method for tempering an adjustment of an image to account for prior adjustments to the image. The adjustment in some embodiments is an automatic exposure adjustment. The method performs an operation for a first adjustment on a first set of parameters (e.g., saturation, sharpness, luminance). The method compares the first set of parameters to a second set of parameters to produce a third set of parameters that expresses the difference between the first adjustment and a second adjustment. The method performs a third operation to produce an adjusted image. The first set of parameters quantify a set of prior adjustments to the image by an image capturing device when the image was captured in some embodiments. The second set of parameters is a set of target parameters. The third set of parameters specify the tempered adjustment of the image.

Abstract: Some embodiments of the image editing and organizing application described herein provide an automatic enhancement process that includes vibrancy adjustment. The vibrancy adjustment increases the saturation of multiple pixels. The saturation of each pixel is determined by subtracting the lowest component value from the highest component value. The process determines an overall saturation of the image using a histogram. The histogram is generated using doubled saturation values for pixels with blue and green as the highest component value.

Abstract: Techniques to improve image fusing operations using intensity mapping functions (IMFs) are described. In one approach, when a reference image's pixel values are within its' IMF's useful range, they may be used to generate predicted secondary image pixel values. When the reference image's pixel values are not within the IMF's useful range, actual values from a captured secondary image may be used directly or processed further to generate predicted secondary image pixel values. The predicted and actual pixel values may be used to construct predicted secondary images that may be fused. In another approach, the consistency between pixel pairs may be used to generate consistency-based weighting factors that may be used during image fusion operations.

Abstract: Provided is an image processing apparatus which includes a histogram generating unit that generates a histogram representing an appearance frequency distribution of a pixel value of an input image, and a quantization table generating unit that generates a quantization table including table information used to perform transform of a bit depth of the pixel value of the input image and table information used to allocate an effective pixel in which an appearance frequency in the histogram generated by the histogram generating unit is not zero to an index value after bit depth transform so that effective pixels are allocated to index values as equally as possible.

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

Abstract: An image processing method extracts line segment elements from grayscale captured images, so that line segments are extracted at high-speed without being influenced by contrast ratio, even if morphology processing is used. A selection processing select an area where continuous line segments possibly exist from the captured image and a morphology processing detect line segment elements in the selected area by scanning an operator. Line segments can be extracted in a plurality of directions at high-speed. Also by an extraction target area selection processing, an area of which contrast ratio is low, continuing from an area of which contrast ratio is high in the line segment growth direction is also extracted as one line segment.

Abstract: Techniques and tools for high dynamic range (HDR) image rendering and generation. An HDR image generating system performs motion analysis on a set of lower dynamic range (LDR) images and derives relative exposure levels for the images based on information obtained in the motion analysis. These relative exposure levels are used when integrating the LDR images to form an HDR image. An HDR image rendering system tone maps sample values in an HDR image to a respective lower dynamic range value, and calculates local contrast values. Residual signals are derived based on local contrast, and sample values for an LDR image are calculated based on the tone-mapped sample values and the residual signals. User preference information can be used during various stages of HDR image generation or rendering.

Abstract: A method and system operative to process color image data are disclosed. In one embodiment, the method can comprise the steps of receiving color image data, determining the color ranges to be applied to the color image data, assigning each of the pixel positions in the image data a color range, assigning a different spatial binary pattern to each color range, and assigning each of the pixel positions a binary output pixel value that corresponds to the spatial binary pattern assigned to the color range assigned to that pixel position. The resulting binary image data can be written to a file for subsequent storage, transmission, processing, or retrieval and rendering. In other embodiments, a system can be made operative to accomplish the same.

Abstract: Embodiments of the present invention relate to a data processing method comprising the steps of processing a first sample set associated with first results of tracking a target in a number of image frames using a first object classifier arranged to operate according to a first feature and processing a second sample set associated with second results of tracking the target in said number of image frames using a second object classifier arrange to operate according to a second feature, and using at least one of the first and second tracking results to influence at least one particle filter adapted to influence at least one of subsequent first and second tracking results.

Abstract: A method of determining locations of at least two pointers in a captured image frame comprises generating a vertical intensity profile (VIP) from the captured image frame, the VIP comprising peaks generally corresponding to the at least two pointers; determining if the peaks are closely spaced and, if the peaks are closely spaced, fitting a curve to the VIP; analyzing the fitted curve to determine peak locations of the fitted curve; and registering the peak locations as the pointer locations.

Abstract: A first video picture is translated based upon a first translation matrix to adjust a contrast of the first video image. A second translation matrix is determined based upon a first histogram of a second video picture. A third translation matrix is determined based upon the first translation matrix and the second translation matrix, and the video picture is translated based upon the third translation matrix. The translation matrix can be determined using a histogram that has been adjusted using a clipped histogram equalization technique.

Abstract: A method of processing data associated with fluorescent emissions from a microfluidic device. The method includes performing an auto-focus process associated with a first image of the microfluidic device and performing an auto-exposure process associated with the first image of the microfluidic device. The method also includes capturing a plurality of images of the microfluidic device. The plurality of images are associated with a plurality of thermal cycles. The method further includes performing image analysis of the plurality of captured images to determine a series of optical intensities and performing data analysis of the series of optical intensities to provide a series of change in threshold values.

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: One embodiment of the present invention provides a system for applying a bilateral filter to an image. During operation, the system selects a first region within the image which is associated with a first pixel. Next, the system constructs a first histogram using pixel values within the first region. The system then computes a new value for the first pixel using the current value of the first pixel and the first histogram. The system then selects a second region within the image which is associated with a second pixel. Next, the system determines a non-overlapping region between the first region and the second region. The system then constructs a second histogram using the first histogram and pixel values in the non-overlapping region. Next, the system computes a new value for the second pixel using the current value of the second pixel and the second histogram.

Abstract: A range map of a visual scene generated by a stereo vision and associate image processing system, and is filtered to remove objects beyond a region of interest and for which a collision is not possible, and to remove an associated road surface. Objects clustered in range bins are separated by segmentation. A composite range map is generated using principale components analysis and processed with a connected-components sieve filter. Objects are identified using one or more of a harmonic profile and other features using an object recognition processor using a combination of inclusive, exclusive and harmonic networks to generate a classification metric.