Abstract: The invention provides a method, system, and program product for detecting an object in a digital image. In one embodiment, the invention includes: deriving an initial object indication mask based on pixel-wise differences between a first digital image and a second digital image, at least one of which includes the object; performing an edge finding operation on both the first and second digital images, wherein the edge finding operation includes marking added edges; generating a plurality of straight linear runs of pixels across an image containing the object, wherein each of the plurality of straight linear runs starts and ends on an added edge and is contained within the initial object indication mask; and forming a final object indication mask by retaining only pixels that are part of at least one of the plurality of straight linear runs.

Abstract: A method, apparatus and program product are provided for simplifying electro-optical imaging data. Spectral/temporal data is received. The spectral/temporal data is formulated into a vector/matrix. Feature extraction analysis is performed. At least two largest principal components are determined from the feature extraction analysis. A cluster diagram is created from the at least two largest principal components. A distance metric is evaluated from the cluster diagram. And, a largest metric is selected based on the distance metric.

Abstract: A method to generate a histogram matched image in which a portion of a first reference image is partitioned into a plurality of regions. Histogram matching is performed separately on the plurality of regions of the first reference image and corresponding regions in a second image to generate a plurality of first histogram matched reference images. Histogram matching is also performed on the portion of the first reference image and a corresponding portion in the second image to generate a second histogram matched reference image. An area from one of at least a first histogram matched reference image and the second histogram matched reference image is selected to generate a finalized histogram matched reference image.

Abstract: A method includes receiving an image of a face to match with images of known faces, extracting blocks multiple blocks from the received image, calculating local binary pattern histograms for each block, generating matching scores for each block against block of the images of known faces, determining a top number, N, of matching scores less than the number of blocks, and matching the received image to an image of a known face as a function of the top number of matching scores.

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: Cell phones and other portable devices are equipped with a variety of technologies by which existing functionality is improved, and new functionality is provided. Some aspects relate to imaging architectures, in which a cell phone's image sensor is one in a chain of stages that successively act on instructions/data, to capture and later process imagery. Other aspects relate to distribution of processing tasks between the device and remote resources (“the cloud”). Elemental image processing, such as filtering and edge detection—and even some simpler template matching operations—may be performed on the cell phone. Other operations are referred out to remote service providers. The remote service providers can be identified using techniques such as a reverse auction, though which they compete for processing tasks. Other aspects of the disclosed technologies relate to visual search capabilities, and determining appropriate actions responsive to different image inputs.

Abstract: An object area containing a text or a graphic is extracted from a document image containing the text or the graphic. Then, on the basis of the extracted object area and stored size information, a cropping area is determined that surrounds the object area with given margins. Further, setting of margins is received. Then, on the basis of the object area and the received setting of the margins, the cropping area is determined. Then, the cropping area determined on the basis of the object area and the size information or alternatively the cropping area determined on the basis of the object area and the setting of the margins is cropped from the document image.

Abstract: A method of initially estimating a front view portion of a photographed image and separating the photographed image into a front view and a background without user interaction and apparatus performing the method are provided. The method of separating a front view and a background of an image includes dividing one or more pixels included in a photographed image into pixel groups according to color similarity between the pixels, estimating the position of the front view in the image divided into the pixel groups, and separating the front view and the background based on the estimated position of the front view. The method automatically separates the front view and the background of the image without a user input.

Abstract: A method and apparatus for encoding an image is provided. An image coding unit, including a region that deviates from a boundary of a current picture, is divided to obtain a coding unit having a smaller size than the size of the image coding unit, and encoding is performed only in a region that does not deviate from the boundary of the current picture. A method and apparatus for decoding an image encoded by the method and apparatus for encoding an image is also provided.

Abstract: The present invention relates generally to an improved system and methods for identifying, assessing, obtaining, evaluating, processing and displaying information about specific topics of interest. In certain embodiments, information is processed with advanced computation and analytical techniques in which detailed statistical data is generated and refined to produce meaningful quantitative and qualitative information that may be useful in analyzing, for example, the economic performance of specific businesses or geographical regions of interest.

Abstract: Various embodiments enable regions of text to be identified in an image captured by a camera of a computing device for preprocessing before being analyzed by a visual recognition engine. For example, each of the identified regions can be analyzed or tested to determine whether a respective region contains a quality associated with poor text recognition results, such as poor contrast, blur, noise, and the like, which can be measured by one or more algorithms. Upon identifying a region with such a quality, an image quality enhancement can be automatically applied to the respective region without user instruction or intervention. Accordingly, once each region has been cleared of the quality associated with poor recognition, the regions of text can be processed with a visual recognition algorithm or engine.

Abstract: The Embodiments provides a method for detecting leakage stage associated with a multimedia. The method includes storing histograms associated with various stages of the multimedia. Further, the method includes receiving candidate histograms associated with various stages of a candidate multimedia, matching the stored histograms with the candidate histograms, and detecting a leakage stage associated with the multimedia in response to a match.

Abstract: A method of classifying the shot type of a video frame, comprising loading a frame, dividing the frame into field pixels and non-field pixels based on a first playfield detection criteria, determining an initial shot type classification using the number of the field pixels and the number of the non-field pixels, partitioning the frame into one or more regions based on the initial classification, determining the status of each of the one or more regions based upon the number of the field pixels and the non-field pixels located within each the region, and determining a shot type classification for the frame based upon the status of each the region.

Abstract: A video processing device includes a histogram generating component, an analyzing component, a comparator and an encoding component. The histogram generating component can generate a histogram for image data of an image frame. The analyzing component can analyze the histogram, can identify an isolated spike in the histogram and can output at least one strobe parameter. The comparator can compare the at least one strobe parameter with at least one predetermined threshold, can output a first instruction signal when the at least one comparison operation is indicative of a strobe and can output a second instruction signal when the at least one comparison operation is not indicative of a strobe. The encoding component can encode the image data in a first manner based on the first instruction signal and can encode the image data in a second manner based on the second instruction signal.

Abstract: The invention particularly relates to a method for identifying an image acquisition feature of a digital image oriented in a coordinate system having a reference axis. According to the invention, this method comprises the steps of: (A) detecting the contours of each distinctive element of the image; -(B) forming a list including each contour constituted by a rectilinear segment; (C) searching, in the list of rectilinear contours, a pair of significant rectilinear segments; (D) in the case where step (C) is successful, checking for a condition of relative symmetry of the significant rectilinear segments with respect to the reference axis; and (E) producing, respectively in the case where step (D) is successful and in the case where one of steps (C) and (D) fails, a data respectively representative of the presence and absence of perspective in the image acquisition, with respect to the reference axis.

Abstract: Disclosed is a software routine which determines which photographs in a corpus are similar, groups the similar photographs, and which then determines which photographs within a group meet criteria of “better” photographs.

Abstract: System and method for image detection that include collecting image data; at a processor, over a plurality of support regions of the image data, computing a dimensionality component of a support region of the image data, wherein the, non-nucleus pixels of a support region; calculating a normalizing factor of the dimensionality component; for at least one weighted pattern of a pattern set, applying a weighted pattern to the dimensionality component to create a gradient vector, mapping the gradient vector to a probabilistic model, and normalizing the gradient vector by the normalizing factor; condensing probabilistic models of the plurality of support regions into a probabilistic distribution feature for at least one cell of the image data; applying a classifier to at least the probabilistic distribution feature; and detecting an object in the image data according to a result of the applied classifier.

Abstract: Segments of interest within video footage are identified automatically. Such segments of interest include portions of the footage which were taken using a hand held camera and which show a static subject, portions which track the motion of a moving subject, and portions which show an abrupt event. Methods are presented for identifying such segments, based on motion and/or colour analysis of the video footage or based on observations of discontinuities in the video footage following a period of stability.

Abstract: An imaging device includes a first detection part which detects one or more subjects in an image captured by the image capturing part capturing an image continuously; a second detection part which follows the one or more subjects detected; and a system control part which includes a setting part setting a part of the image as a limited region, and causes, after the first detection part detects the one or more subjects in the captured image, the second detection part to follow and detect a subject in an image captured subsequently to the captured image, and causes the first detection part to detect a subject in the limited region.

Abstract: There is provided a method of processing a digital image including: (a) obtaining a plurality of images; (b) converting the plurality of images into histograms; (c) setting one of the plurality of images as a reference image and another of the plurality of images as a comparison target image; (d) adjusting a distribution of the histogram of the reference image to match a distribution of the histogram of the comparison target image to produce an adjusted reference image; (e) comparing a difference between the adjusted reference image and the comparison target image to produce a masking image; (f) applying the masking image to the comparison target image to produce an adjusted comparison target image; and (g) combining the reference image and the adjusted comparison target image to produce a high dynamic range (HDR) image. Accordingly, even if there is a complex motion on a subject, a clear image without an image overlap or a ghost effect may be obtained when producing the HDR image.

Abstract: There are provided an image processing apparatus, image processing method, and a computer-readable, non-transitory medium that can determine with high accuracy whether or not an input image contains a background element. The image processing apparatus includes a decimated image generator for generating a decimated image through pixel decimation from an input image, an edge pixel extractor for extracting edge pixels from the decimated image, an edge class extractor for extracting an isolated edge pixel from among the edge pixels, a histogram generator for generating an isolated histogram based on the isolated edge pixel, and a decision unit for making, based on the isolated histogram, a decision as to whether or not the input image contains a background element.

Abstract: Objects in a range map image are clustered into regions of interest responsive to range as determined from either a separate ranging system or from a top-down transformation of a range map image from a stereo vision system. A relatively-central location of each region of interest is transformed to mono-image geometry, and the corresponding portion of an associated mono-image is searched radially outwards from the relatively-central location along a plurality of radial search paths, along which the associated image pixels are filtered using an Edge-Preserving Smoothing filter in order to find an edge of the associated object along the radial search path. Edge locations for each of the radial search paths are combined in an edge profile vector that provides for discriminating the object.

Abstract: A video analysis apparatus may include a generating unit to generate at least one spatiotemporal pattern by performing pixel sampling on a plurality of frames in an input video, an extracting unit to extract at least one region of interest having a sinusoidal pattern from the at least one spatiotemporal pattern, and an analysis unit to perform a frequency analysis of the at least one region of interest to determine whether the input video includes a predetermined type of content.

Abstract: A method of receiving input from a user includes sensing a first trajectory of a center of mass of a hand of the user during a gesture made by the hand. A second trajectory of a finger tip of the hand of the user during the gesture made by the hand is also sensed. An alphanumeric character represented by the gesture made by the hand is determined dependent upon both the first trajectory and the second trajectory.

Abstract: There are provided an image processing apparatus, image processing method and a computer-readable, non-transitory medium that can binarize the input image so that the characters can be differentiated with high accuracy from the background area. The image processing apparatus includes an edge pixel extractor for extracting edge pixels from an input image, a first histogram generator for generating a first histogram based on a luminance value of each of the edge pixels, a second histogram generator for generating a second histogram based on a minimum luminance value among the luminance values of pixels neighboring each of the edge pixels, a static threshold calculator for obtaining a static threshold based on the first histogram and the second histogram, and a binarization unit for binarizing the input image by using the static threshold.

Abstract: Disclosed herein is a method for auto-depicting trends in object contours (referred to as ADTOC). At the heart of ADTOC is a sifting process to determine a significant angular value via evaluating a plurality of angular values in a predefined range. ADTOC is characterized in that a probe-ahead concept is applied to obtain a reference angular value along the current route, and then the probed angular value is used to modify the significant angular value in order to timely correct the subsequent trace direction, thus achieving more accurate trace result. Contours with discontinuous segments caused by noise, obstacles, illumination, shading variations, etc. can also be auto-depicted without requiring a predefined auxiliary route.

Abstract: A method for determining a frontal face pose by using the symmetry of a face including detecting a face region in an image, detecting an eye region in the detected face region, normalizing the face region, analyzing the symmetry in the normalized face region, and determining whether a face pose is a frontal face pose based on an analysis of the symmetry.

Abstract: A method and apparatus for detecting and compensating for a backlight frame are provided. The method includes receiving data regarding a current frame comprising pixels that are expressed by a luminance component and one or more chrominance components; and determining whether the current frame is a backlight frame based on values of the one or more chrominance components of the pixels.

Abstract: Aspects of the present invention are related to systems and methods for automatically extracting, from a document image, references to relevant external content and automatically retrieving the external content associated with the references.

Abstract: A method comprises extracting a local identifier (130, 730a, 730b) from an image (100, 500, 700), the image (100, 500, 700) also having positional data (120) relating to the location at which the image (100, 500, 700) was captured; and associating the extracted local identifier (130, 730a, 730b) with the corresponding positional data (120) to allow for associating the extracted local identifier with a digital map (300, 600, 800).

Abstract: Systems and methods for measuring consistency between two objects based upon a rank of object elements instead of based upon the values of those object elements. Objects being compared can be represented by d-dimension feature vectors, U and V, where each dimension includes an associated value. U and V can be converted to rank vectors, P and Q, where values of U and V dimensions are replaced by an ordered rank or a function thereof. Analysis directed to the consistency between U and V can be accomplished by determining consistency between P and Q, which can be more efficient and more accurate, particularly with regard to illumination-invariant comparisons.

Abstract: Image forming apparatus (100) creates a toner pattern on intermediate transfer belt (11) as a preprocessing of gradation correction, and calculates a cycle at which density unevenness is largest. Then, a toner image for gradation correction is formed so as to cancel cyclic unevenness at a cycle at which the largest density unevenness occurs. As a result of this, it becomes possible to suppress the deterioration of density detection accuracy and perform a highly accurate gradation correction even if density unevenness of any cycle occurs.

Abstract: A method and system for mapping colors of an image. The method including the steps of: segmenting an image into a plurality of regions, so that pixels in each of the plurality of regions have a characteristic that meets a predetermined similarity; determining an initial contrast between adjacent regions in the plurality of regions; and transforming an initial color of each of the plurality of regions into a target color; where a target contrast between the adjacent regions in the plurality of regions is equal to or greater than the initial contrast or a difference between the target contrast and corresponding initial contrast is less than a predetermined threshold; and where at least one of the steps is carried out by a computer device.

Abstract: According to one embodiment, a display apparatus includes a light modulating unit, a light source unit, a luminance setting unit, a luminance distribution calculating unit, a signal level converting unit, and a control unit. The light source unit includes a basic light source and an extended light source illuminating each of divisional areas into which the display area tentatively divided. The basic light source emits white light with first emission peak wavelengths. The extended light source emits light with a second emission peak wavelength being different from the first emission peak wavelengths and being within a range between shortest and longest wavelengths of the first emission peak wavelengths. The control unit is configured to generate a control signal controlling the basic light source and the extended light source so as to provide a period in which the basic light source and the extended light source simultaneously emit light.

Abstract: A method, including automatically identifying, by a processor, a region of a digital image containing first pixels, each situated on a positive horizontal gradient, and second pixels in proximity to the first pixels, each situated on a negative horizontal gradient. A distribution of intensities of a color channel is then calculated for the pixels in the region, and the distribution is analyzed in order to detect whether the region contains anti-aliased text.

Abstract: A system and method to classify forms. An image representing a form of an unknown document type is received. The image includes line-art. Further, a plurality of template models corresponding to a plurality of different document types is received. The plurality of different document types is intended to include the correct document type of the unknown document. A subset of the plurality of template models are selected as candidate template models. The candidate template models include line-art junctions best matching line-art junctions of the received image. One of the candidate template models is selected as a best candidate template model. The best candidate template model includes horizontal and vertical lines best matching horizontal and vertical lines of the received image, respectively, aligned to the best candidate template model.

Abstract: A digital image processing apparatus recognizes an image of a firework and performs image quality processing on the image. The digital image processing apparatus for recognizing a firework may include a digital signal processor (DSP) that recognizes a firework in a scene recognition mode based on data regarding luminance and size of flames of the firework of a live view image including at least two consecutively input frames, and that performs image quality processing on the live view image.

Abstract: A method and apparatus for detecting and recognizing an object using a vector histogram based on a local binary pattern are disclosed. The apparatus of detecting and recognizing an object using a local binary pattern includes: a feature map creator configured to extract an object area in which a moving object exists from an input image, to create a local binary pattern by designating a local area in the object area, and to create a vector component map including information about magnitude vector components and direction vector components using the local binary pattern; a feature map configuring unit configured to divide the object area into a plurality of blocks and to create a feature vector map through a histogram using the vector component map in a unit of the block; and an object detector configured to detect and classify the moving object based on the feature vector map.

Abstract: Techniques for calibrating a classification system, wherein one or more objects in at least one video are classified, are provided. At least one view associated with the at least one video is obtained. The at least one view is partitioned into at least one region. A given object is classified in accordance with its location in reference to the at least one region. In an additional embodiment, one or more object models are obtained. At least one normalized size of the one or more objects is defined within at least one view associated with the at least one video in accordance with the one or more object models. The one or more objects are classified in accordance with the at least one defined normalized size.

Abstract: A system for image processing includes determining edge pixels of a model image using an edge based technique and determining an angular orientation for each the edge pixels of the model image. The system determines a histogram of gradient orientations based upon the angular orientations of the model image. The system determining edge pixels of an input image using an edge based technique and determining an angular orientation for each of the edge pixels of the input image. The system determines a histogram of gradient orientations based upon the angular orientations of the input image. The system compares the histogram of gradient orientations of the model image with the histogram of gradient orientations of the input image to determine candidate locations of an object within the input image.

Abstract: A local feature amount calculating device includes a local feature amount calculating unit that acquires a local feature amount of a feature point for each pixel by giving a vote of a strength of the direction of a pixel, which is calculated by a direction strength calculating unit, to a vote cell to which a pixel of interest belongs out of vote cells of a rotated vote cell pattern that is acquired by rotating a reference vote cell pattern by an angle corresponding to a main axis direction along a corrected edge gradient direction that is acquired by correcting an edge gradient direction of the pixel that is calculated by a direction strength calculating unit in accordance with the main axis direction.

Abstract: A system computes a vectorial representation for each of a set of initial patches in an image and compares the vectorial representation for each initial patch with vectorial representations of nearby patches. Each nearby patch is within a distance from an initial patch. The system applies an ordinal coding algorithm on the comparison results between the vectorial representations for the initial patches and vectorial representations of nearby patches to generate a two-dimensional representation of the image indicating a repeating pattern within the image.

Abstract: There is provided a video processing apparatus comprising a motion vector detection unit for detecting data on the motions of objects by using at least two frames, an interpolation frame generation unit for generating interpolation frames in the horizontal/vertical and temporal directions in accordance with the motion vectors obtained by the motion vector detection unit, and an image feature detection unit for detecting the features of motions extended over the at least two frames, wherein the procedures, performed by the image feature detection unit, of generating interpolation frames in the horizontal/vertical and temporal directions are switched over in accordance with the features of motions.

Abstract: There is provided an image processing apparatus which can suppress degradation of an image quality in a recording material save mode processing and obtain an effect of consumption amount reduction of recording material desired by a user at low costs. A recording material consumption amount at the time of applying first color conversion processing unit is predicted corresponding to inputted image data. The setting of a second color conversion processing is changed from a prediction value and a target value of the recording material consumption amount.

Abstract: Methods, systems, and computer readable media with executable instructions, and/or logic are provided for incremental image clustering. An example method for incremental image clustering can include identifying, via a computing device, a number of candidate nodes from among evaluated leaf image cluster (LIC) nodes on an image cluster tree (ICT) based on a similarity between a feature of a new image and an average feature of each of the evaluated LIC nodes. The evaluated nodes include at least one node along each path from a root node to either a leaf node or a node having a similarity exceeding a first threshold. A most-similar node can be determined, via the computing device, from among the number of candidate nodes. The new image can be inserted to a node associated with the determined most-similar node, via the computing device.

Abstract: A computerized method determines a similarity between a first image and a second image. The first image is converted into a first grayscale image, and the second image is converted into a second grayscale image. A first feature vector of the first grayscale image and a second feature vector of the second grayscale image are extracted. A similarity value is calculated indicating the similarity between the first image and the second image according to the first feature vector and the second feature vector. If the similarity value is greater than or equal to the predetermined threshold, the first image is similar to the second image and a determination result is outputted denoting the first image is similar to the second image.

Abstract: A system and method for performing object or context-based categorization of an image is described. A descriptor for image regions, which is represented by a histogram of oriented uniform patterns, is described. The descriptor is compared to descriptors of other images to determine a similarity score that accounts for distinctiveness, reducing perceptual aliasing. Additionally, a kernel alignment process considers only the descriptors that are determined to be most informative.

Abstract: System and method embodiments are provided to enable features and functionalities for automatically detecting and localizing the position of an object in a video frame and tracking the moving object in the video over time. One method includes detecting a plurality of objects in a video frame using a combined Histograms of Oriented Gradients (HOG) and Local Binary Pattern (LBP) algorithm, highlighting the detected objects, and tracking one of the detected objects that is selected by a user in a plurality of subsequent video frames. Also included is a user device configured to detect a plurality of objects in a video frame displayed on a display screen coupled to the user device using a combined HOG and LBP algorithm, highlight the detected objects, and track one of the detected objects that is selected by a user in a plurality of subsequent video frames on the display screen.

Abstract: An image processing apparatus is disclosed which includes: an acquisition section configured to acquire image data of an image; a histogram calculation section configured to calculate a histogram of the acquired image data; a histogram storage section configured to store the calculated histogram that is updated sequentially; and a change determination section configured to determine whether a change has occurred in the acquired image based on the degree of similarity between the calculated histogram and the previously stored histogram.

Abstract: According to one embodiment, a method of classifying a feature in a video sequence includes selecting a target region of a frame of the video sequence, where the target region contains the feature; dividing the target region into a plurality cells, calculating histograms of optic flow with the cells comparing the histograms of optic flow for pairs of cells; and assigning the feature to a class based at least in part on the result of the comparison.