Abstract: Provided is an image processing apparatus which includes a block histogram generation unit configured to calculate frequency of a pixel value in each block, divide a dynamic range, and generate a first histogram including “N” number of bins, a pixel histogram generation unit configured to calculate frequency of a target pixel in a block based on first histograms of the block including the target pixel and a block adjacent to the block including the target pixel, and generate a second histogram including “N” number of bins for each pixel, and an output value determination unit configured to generate a relation between the pixel value and an output value of the pixel value based on the second histogram so that a maximum cumulative frequency of the second histogram matches a maximum value of the output value, and calculate the output value based on the pixel value of the target pixel.

Abstract: A character string recognition method for recognizing a character string may include a first step in which a first projection data of image data are calculated in a direction of the character string and a second step in which a position of the character string is detected on the basis of the first projection data. In the first step, the image data are divided into a plurality of segments in the direction of the character string and projection in the segment is calculated. The method may further include a third step in which a second projection data in the segment are calculated on the basis of the position of the character string and a fourth step in which a position where the second projection data exceeds a threshold value is detected as a boundary position of a character, and the threshold value may be changed according to pixel number between both ends of the character string.

Abstract: An image processing apparatus includes: a unit producing a histogram in a color space from an input image; a unit extracting a plurality of peak colors having a local maximum frequency of appearance of a color value in the histogram; a unit determining whether to unify the extracted plurality of peak colors, based on a feature amount of the extracted plurality of peak colors, and selecting a peak color as a representative color when the extracted plurality of peak colors are unified, the feature amount being a lightness difference among the extracted plurality of peak colors and directions of vectors in the color space, the vectors each showing a shortest distance from one of the extracted plurality of peak colors to a line segment connecting between a reference color and a dark color; and a unit replacing a color of each pixel in the input image by the representative color.

Abstract: A driver assistance system for a vehicle includes an imaging device having a field of view forward of a vehicle and an image processor operable to process image data captured by the imaging device. The vehicle includes a control system operable at least in part to control the speed of the vehicle. The control system may reduce the speed of the vehicle responsive at least in part to a detection of a curve in the road ahead of the vehicle via processing by the image processor of image data captured by the imaging device. The control system may control the speed of the vehicle to a reduced speed for traveling around the detected curve in the road, and may increase the speed of the vehicle to above the reduced speed when the vehicle is traveling along a straighter section of road after the curve in the road.

Abstract: A method of enhancing contrast includes obtaining a first luminance histogram of an input image; generating a second luminance histogram through pixel redistribution for the first luminance histogram; computing a conversion function based on both a first cumulative density function based on the first luminance histogram and a second cumulative density function based on the second luminance histogram; and changing the luminance distribution of the input image based on the conversion function.

Abstract: A method for efficiently calculating signal thresholds for use in signal processing is described. The method computes and stores a cumulative histogram and a weighted cumulative histogram. The method then provides a first estimate for a threshold based on a single ratio. The method next performs an iterative computation to get to the ultimate threshold result. Method iterations only require multiplication and addition operations on the stored values making the method well suited for implementation in fixed-point digital signal processors.

Abstract: Relative histograms compare occurrences in event channels for a multi-channel data set for determining comparisons therebetween. One or more relative histograms are formed using relating functions applied to channels, preferably including a quotient between a first reference channel and a second channel and between the reference channel and at least a third channel. Preferably the relating functions generate values where a ratio and its reciprocal are symmetrical about an identity value. More preferably a data set is presented in a two-dimensional histogram for establishing the deviation of significant counts from an adjustment point which is preferably at the identity value. In practice, the relative histograms can be applied to correct tint in the red, green and blue channels of color images.

Abstract: A method to assess signal transmission quality and the adjust method thereof are proposed. First, different time points of a control signal at a receiving end are acquired and the number of signal transitions in a predetermined time interval is counted. Next, the number of signal transitions is recorded and compared to a reference value to obtain a comparison result. The quality of the control signal is then determined based on the comparison result. The parameter setting of the receiving end is adjusted according to the quality of the control signal received by the receiving end to get a better performance setting.

Abstract: Image determining apparatuses, image enhancement apparatuses, backlight image enhancement apparatuses, and backlight image enhancement methods are provided.

Abstract: Image determining apparatuses, image determining methods, image enhancement apparatuses, and image enhancement methods are provided. An image determining apparatus according to an exemplary embodiment of the present invention includes: (A) a histogram data generation section; (B) an attribute information obtaining section; and (C) a determining section.

Abstract: Systems and methods for segmenting an image into at least two layers, a foreground and a background layer include rough labeling or segmenting at least a portion of the image into foreground and background pixels. The rough labeled pixels may be refined by using local classifications. Additional processes may be performed on the image including, but not limited to, filtering, image enhancing, shape refining, image compression, etc.

Abstract: Exemplary embodiments of the present invention are directed to a method for automatically selecting images, from among multiple images, for sequential display, comprising: establishing a total time for a sequential display of a set of selected images; clustering images into groups; ordering the images based on image quality; and selecting at least one of the images within a selected group based on the image quality and total time for inclusion in the set of selected images.

Abstract: A method, system and computer-readable medium of filtering noise pixels and other extraneous data, including saturated fat tissue and air data in image data is provided. Examples of image data may include but are not limited to magnetic resonance imaging data and computed tomography data. The method includes receiving pixel count for each signal intensity value of the image data; determining a signal intensity value, Ipeak, corresponding to a pixel count of a greatest number of pixels, Npeak; setting a noise threshold at a signal intensity value, Inoise, corresponding to a pixel count, NI, such that NI is determined based on Npeak; and filtering from the image data one or more pixels with signal intensity values below the noise threshold. NI may be determined such that NI=Npeak/3 or close to Npeak/3.

Abstract: An image processing apparatus generates, for an image, partial histograms by dividing a luminance histogram at downward convex parts of a frequency distribution of the luminance histogram. The image processing apparatus calculates, for a partial histogram selected from the partial histograms, a difference between a maximum frequency in each of all the partial histograms located on the first side of the selected partial histogram, and a minimum frequency within a luminance range from a luminance level of the maximum frequency to that of a maximum frequency in the selected partial histogram as a drop, and sets a maximum one of the drops calculated for the respective partial histograms as a drop. The image processing apparatus sets a weight, which becomes smaller as this drop is larger, for the selected partial histogram, and calculates a weighted average of the luminance histogram, thereby acquiring a luminance value for the tone correction.

Abstract: A method for merging histograms may include generating a histogram for a region of an image, the histogram including bucket values representing a count of pixels having the same pixel value or a weighting dependent on the pixels. The method may include maintaining an array of values indicating non-zero histogram entries for a group of bucket values (e.g., a count of non-zero bucket values in the group or a bitmask indicating if each bucket value is non-zero). A sparse histogram for which such an array exists may be merged with a second histogram. Merging the histograms may include not merging any bucket values in the group if the associated array value is zero, and merging some or all of the bucket values if it is non-zero. The methods disclosed may be implemented by program instructions executing in parallel on CPU(s) or GPUs.

Abstract: A method and apparatus for identifying pathology in a brain image comprises the steps of firstly determining the location of the midsagittal plane (MSP) of the brain illustrated in the image under examination by identifying the symmetry of the two hemispheres based on the determination of up to 16 approximated fissure line segments (AFLSs). Those AFLSs with a larger angular deviation from the MSP than a predefined threshold are considered as outlier AFLSs while the rest are taken as inlier AFLSs. The ratio of the number of the outlier AFLSs to the number of inlier AFLSs is then calculated. A comparison of the ratio with a further predetermined threshold value is made and if the ratio exceeds the further predetermined threshold value, pathology is present in the brain image.

Abstract: A driver assistance system for a vehicle includes an imaging device having a field of view forward of a vehicle and in a direction of travel of the equipped vehicle, an image processor operable to process image data captured by the imaging device, and a global positioning system operable to determine a geographical location of the vehicle. The equipped vehicle includes an adaptive speed control system for controlling the speed of the equipped vehicle. The adaptive speed control system may reduce the speed of the equipped vehicle responsive at least in part to a detection of a curve in the road ahead of the equipped vehicle via processing by the image processor of image data captured by the imaging device.

Abstract: A method for generating an image includes accessing data of a scan of an object, using at least one characteristic of the accessed data to delineate at least one item of interest in the data and generating a 3D visualization image wherein transparency levels for at least some pixels not representing the item of interest are set according to a first set of rules, and transparency levels for at least some pixels representing an interior portion of the item of interest are set according to a second set of rules different than the first set of rules, and at least some pixels representative of a transition area are set according to a third set of rules different than the first and second sets of rules.

Abstract: Aspects of the present invention relate to methods and systems for segmenting a digital image into regions. A frequency-of-occurrence of image values may be determined excluding a portion of pixels in a digital image. An image value associated with a peak in the frequency-of-occurrence of image values may be identified and associated with an image label. Pixel locations may be labeled based on the associated labels and image values. Additionally, unreliable pixels may be determined and labeled based on the associated labels and image values.

Abstract: An image processing apparatus according to the present invention, comprises a histogram creation unit creates a histogram from an input image, a detection unit detects a gradation level of interest from the histogram, a gradation correction parameter generation unit generates a gradation correction parameter to improve a gradation characteristic in a gradation range around the gradation level of interest, and a correction unit corrects the gradation of the image using the gradation correction parameter, wherein the detection unit detects, as the gradation level of interest, a gradation level of which 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 color image processing device configured to process input color image data includes a specifying unit configured to specify a gray region including a gray axis within a color gamut of the input color image data in a color space, a first setting unit configured to set a first gray stabilization region away from the gray axis in the color space so as to satisfy a predetermined condition, and a first transferring unit configured to transfer each color within the gray region specified by the specifying unit into the first gray stabilization region.

Abstract: A method for enhancing an ultrasound image is provided, wherein the ultrasound image is segmented into a feature region and a non-feature region, while sufficiently utilizing features contained in the ultrasound image, in particular including some inconspicuous features. The enhanced image according to present invention is not susceptive of the image segmentation and avoid dependence of the enhancement effect on the segmentation template, so as not to produce an evident artificial boundary between the feature region and the non-feature region but to highlight some special information in the image and to remove or mitigate invalid information. Thus the enhanced ultrasound image is particularly suitable for the visual system of the human beings.

Abstract: Near infra-red images of natural scenes usually have better contrast and contain rich texture details that may not be perceived in visible light photographs. The contrast and rich texture details form a NIR image corresponding to a visible light image are useful for enhancing the visual quality of the visible light image. To enhance the visual quality of a visible light image using its corresponding near infra-red image, a computer-implemented method computes a weight region mask from the visible light image, transfers contrast data and texture data from the near infra-red image to the visible light image guided by the weighted region mask. The contrast data is computed from the low frequency subbands of the visible light image and corresponding infra-red image after a wavelet transform by matching the histogram of gradient magnitude. The texture data is computed from the high frequency subbands of both images after wavelet transform.

Abstract: Visualization systems for rendering images from a multi-dimensional data set, include an interactive visualization system configured to accept user input to define at least one explicit prioritized feature in an image rendered from a multi-dimensional image data set. The at least one prioritized feature is automatically electronically rendered with high or full quality in different interactively requested rendered images of the image data while other non-prioritized features are rendered at lower quality. The visualization system may optionally include a rendering system configured to render images by electronically assigning a level of detail for different tiles associated with an image, each level of detail having a number of pixel samples to be calculated to thereby accelerate image processing.

Abstract: An image processing apparatus, image processing method, and program which enable generation of vector data capable of replicating a clipart region of a raw image as faithfully as possible are provided. To accomplish this, a raw image is segmented into region images according to attributes. From the segmented region images, a region image having a predetermined attribute is cut out from the raw image. At least one representative color which configures the predetermined region image is decided based on an appearance color of the cut out predetermined region image. A color image having the decided representative color is extracted from the predetermined region image. A contour line of the extracted color image is extracted. An edge image within the predetermined region image is extracted. The extracted contour line is corrected based on the extracted edge image. Using the corrected contour line, vector data of the predetermined region image is generated.

Abstract: Background images are removed and only desired payment information is extracted from a grayscale image of a check or similar financial instrument. A density distribution improvement process applied to grayscale raw image data 40 acquired by scanning a check corrects the density distribution of the raw image data 40 to separate the density range of the desired payment information from the density range of the background image. A threshold level 44 for clearly separating the payment information from the background image is then calculated from the characteristics of the density distribution of the grayscale improved image data 42 acquired by the density distribution improvement process. Histograms of the density distributions are used to determine the characteristics of the density distribution. The improved image data 42 is then converted to binary image data 46 using the threshold level 44.

Abstract: An image processor computes a raw histogram for an unprocessed raw digital image. The image processor positions a clip point at an intensity level within the raw image histogram. The pixels having an intensity level less than the intensity level of the clip point are blacked-out (reduced in intensity). The remaining illuminated pixels are displayed.

Abstract: A method for reducing spatial noise of images includes the following steps. A target pixel is obtained and an operating block is built accordingly. Pixel values of the target pixel and multiple neighboring pixels in the operating block are operated to obtain a variance corresponding to the operating block. Whether the target pixel is characteristic is judged according to the variance. If the target pixel is not characteristic, the multiple pixels in the operating block are filtered to obtain a modulated pixel value. The pixel value of the target pixel is updated to the modulated pixel value.

Abstract: Correcting pattern noise projection images includes acquiring a set of projection images with an optical tomography system including a processor, where each of the set of projection images is acquired at a different angle of view. A threshold is applied to each projection image produce a set of threshold images. Each threshold image may optionally be dilated to produce a set of dilated images that are summed to form an ensemble image. Each of the dilated images is processed to produce a set of binary images. The set of binary images are summed to form an ensemble mask. The ensemble image is divided by the ensemble mask to yield a background pattern noise image. Each projection image is multiplied by a scaling factor and divided by the background pattern noise to produce a quotient image that is filtered to produce a noise corrected projection image.

Abstract: A driver assistance system for a vehicle includes an imaging device having a field of view forward of a vehicle equipped with the driver assistance system and in a direction of travel of the equipped vehicle. The imaging device is operable to capture image data and an image processor is operable to process image data captured by the imaging device. The equipped vehicle includes an adaptive speed control system for controlling the speed of the equipped vehicle, and the speed of the equipped vehicle is controlled by the adaptive speed control system at least in part responsive to processing by the image processor of image data captured by the imaging device.

Abstract: A peripheral equalization (PE) method and apparatus for compensating for thickness reduction in outer edges of the breast in a mammogram (i.e. a two-dimensional image) while keeping the central area substantially unchanged. The PE method and apparatus can also be applied to three dimensional (tomosynthesis) images of a breast. The peripheral equalization is achieved by segmenting the image of the breast into at least two regions and using a multi-threshold technique to process the data in at least one of the two regions.

Abstract: Background images are removed and only desired payment information is extracted from a grayscale image of a check or similar financial instrument. A density distribution improvement process applied to grayscale raw image data 40 acquired by scanning a check corrects the density distribution of the raw image data 40 to separate the density range of the desired payment information from the density range of the background image. A threshold level 44 for clearly separating the payment information from the background image is then calculated from the characteristics of the density distribution of the grayscale improved image data 42 acquired by the density distribution improvement process. Histograms of the density distributions are used to determine the characteristics of the density distribution. The improved image data 42 is then converted to binary image data 46 using the threshold level 44.

Abstract: A method is disclosed for the generation of a background mask from an intensity-value-coded image with a noisy background area. The method includes generating an intensity value histogram of the image; fitting a model curve to a subarea of the intensity value histogram; calculating a threshold value in the intensity value histogram from the fit parameters of the model curve; and generating the background mask starting from at least one defined image area that belongs to the background noise by adding all the pixels whose intensities are below the threshold value to the background mask when connected to the image area via pixels whose intensities are also below the threshold value.

Abstract: In accordance with an embodiment of the present invention, an assistance mechanism tracks a plurality of time intervals between a plurality of input events. Each input event of said plurality of input events is generated by a user physically manipulating an input device at a client. Based on the plurality of time intervals, the assistance mechanism dynamically determines a threshold period. Then the assistance mechanism determines whether a subsequent input event has been generated within said threshold period. In response to determining that an input event has not been generated within said threshold period, the assistance mechanism may cause information to be displayed at the client.

Abstract: A threshold determination method is selected from among a plurality of alternative global thresholding determination methods and, optionally, a local thresholding determination method based on characteristics of a histogram of grayscales values representing an image. When it is determined to use a global thresholding method, a single global binarization threshold value is determined using the selected global thresholding method. Various alternative global binarization threshold values include a predetermined constant, an average value of the two grayscale values, an Otsu method based threshold value, a Newton method based threshold value, and an Otsu method based threshold value based on a truncated version of the histogram. When it is determined to use local thresholding, a plurality of local binarization threshold values are determined corresponding to different non-overlapping blocks of the image.

Abstract: An analysis method using histograms derived from positron emission tomography (PET) or single photon emission tomography (SPECT) images of the brain, which utilizes radiopharmaceuticals for the detection and diagnosis of pathological targets associated with neurodegenerative disease in a patient is provided.

Abstract: Upon processing a visible light image signal and infrared image signal respectively obtained by illuminating a transparent document with light beams coming from a visible light lamp for mainly emitting visible light and an infrared lamp for mainly emitting infrared light, and photoelectrically converting optical images of the transparent document, a histogram is generated on the basis of the infrared image signal, a threshold value is calculated based on the histogram, and infrared image signal components equal to or smaller than the threshold value are extracted by comparing the calculated threshold value and infrared image signal components. Visible light image signal components corresponding to the extracted infrared image signal components are interpolated using surrounding visible light image signal components.

Abstract: A method to detect anchorperson segment in news reporting by using visual characteristics to provide the basis to divide news into various categories includes steps of providing news image for skin color detection on the image with color space; applying morphology depending on whether the object in the image subject to skin color detection is moving to eliminate noise surrounding the image of the face to solve the region of the face of the anchorperson; and performing anchorperson detection once again by detecting the probable anchorperson segment.

Abstract: A method for enhancing an ultrasound image is provided, wherein the ultrasound image is segmented into a feature region and a non-feature region, while sufficiently utilizing features contained in the ultrasound image, in particular including some inconspicuous features. The enhanced image according to present invention is not susceptive of the image segmentation and avoid dependence of the enhancement effect on the segmentation template, so as not to produce an evident artificial boundary between the feature region and the non-feature region but to highlight some special information in the image and to remove or mitigate invalid information. Thus the enhanced ultrasound image is particularly suitable for the visual system of the human beings.

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 shape of a medical device to be implanted into a subject is verified by acquiring a plurality of inter-fiduciary marker dimensions from the subject. Three-dimensional image data of the markers and a tissue of interest, included in the subject, is obtained. Respective measurements between the fiduciary markers around the subject and in the image data are confirmed. The tissue of interest and the fiduciary markers are identified in the image data. Points of the tissue of interest and the fiduciary markers are rendered as a 3-dimensional surface representation. A 3-dimensional model of the tissue of interest and the fiduciary markers is generated as a function of the surface representation. A shape of the medical device to be implanted into the subject is determined as a function of the 3-dimensional model.

Abstract: A data distribution system in which distribution data is generated by a distribution data generation portion, a second range is specified by a specifying portion, the second range is mapped to a first range by a mapping portion, and third image data is generated by performing binarization based on a threshold value regulated in the first range by various components. In this way, binarization can be suitably performed even when pixel value distribution data differs for each subject.

Abstract: A histogram is generated on the basis of the pixel value of an image. An LUT used for changing the dynamic range of the image is generated on the basis of the histogram value in each pixel value interval of the generated histogram. The dynamic range of the image is changed on the basis of the generated LUT.

Abstract: In certain embodiments, a method for generating fees using a receiving device, involves distributing censored video from a distributor video to a receiving device; and uncensoring the censored video using the receiving device upon payment of a fee. The receiving device uses overlay data received from the distributor to uncensor the censored video by overlaying the overlay data over the censored video using a video overlay frame to overlay a video frame containing the censored video data in accordance with boundaries determined by an alpha plane within the receiving device. This abstract should not be considered limiting since embodiments consistent with the present invention may involve more, different or fewer elements.

Abstract: In a digital signal processing system, a method for selecting a transform function to apply to an input signal based on characteristics of the signal, and for self-adjusting criteria which are used in selecting a transform function to apply to a subsequent signal. Characteristics are obtained from the signal. The characteristics are compared to adjustable criteria which are used in selecting a transform function. Differing criteria are maintained for the different selectable transform functions. A record is maintained of transform functions selected and the particular characteristics that caused the selection. Based on the ability of a transform function to minimally define the coded signal, an inverse transform function is selected to decode the signal. The criteria used in selecting a transform function to apply to a subsequent signal are adjusted based on a quality measure of the decoded signal and the record of selected transform functions.

Abstract: A histogram generating device is disclosed. An embodiment has a brightness signal generating module generating a brightness signal by use of RGB component data of an input frame, an image component data selecting module outputting a single component frame consisting of image component data, which is one of the RGB component data and the brightness signal, an interval histogram generating module generating a level value by calculating the number of image component data belonging to each level grouped by a histogram resolution as a detection interval of the plurality of successive single component frames is changed, and a memory storing a plurality of level values generated for each of the single component frames.

Abstract: An image processing apparatus includes an input unit for inputting image data, an attribute information generation unit for generating attribute information about each pixel of the image data, a block division unit for dividing the image data into a plurality of blocks of a predetermined size, a histogram generation unit for generating a histogram of colors and the number of pixels of each color existing in a focused block divided by the division unit, and a color replacement unit, if it is not determined that the area having the focused color is a significant area, for replacing a color of a pixel existing within the area having the focused color with a different color so that the color of the area having the focused color becomes the same as the color of another area contacting the area having the focused color and having the different color according to a predetermined condition.

Abstract: A method is for correcting inhomogeneities in an image that is recorded from an examination object. The method includes recording an image to be corrected, calculating a correction image from the image to be corrected and correcting the recorded image with the aid of the correction image in order to produce a normalized image by multiplying the correction image by the image to be corrected. When calculating the correction images, the pixels in the vicinity of the imaged examination object are identified with the aid of a signal intensity that is lower than a limiting value. Further, these pixels are allocated signal intensities that in each case are a function of the signal intensity of the pixels in the respective neighborhood.

Abstract: A vehicle environment monitoring device identifies objects from an image taken by an infrared camera. Object extraction from images is performed in accordance with the state of the environment as determined by measurements extracted from the images as follows: N1 binarized objects are extracted from a single frame. Height of a grayscale objects corresponding to one of the binarized objects are calculated. If a ratio of the number of binarized objects C, where the absolute value of the height difference is less than the predetermined value ?H, to the total number N1 of binarized objects, is greater than a predetermined value X1, the image frame is determined to be rainfall-affected. If the ratio is less than the predetermined value X1, the image frame is determined to be a normal frame. A warning is provided if it is determined that the object is a pedestrian and if a collision is likely.

Abstract: A color balance correction device includes a histogram generating unit that generates histograms of a gradation level of pixels for R, G, and B; a decreasing-tendency-area identifying unit that identifies a range that the frequency tends to decrease first from a highlight side of each of histograms generated by the histogram generating unit as the catch light area; and a correction-amount calculating unit that calculates a correction amount of the color balance using data of pixels except for those in the catch light area specified by the decreasing-tendency-area identifying unit.