Abstract: A method using optical coherence tomography to capture the microvascular network of the superficial layer of the finger skin for the purpose of fingerprint authentication and liveness detection. At the dermal papilla region, the vascular pattern follows the same pattern of the fingerprint and this vascular pattern forms a live vascular fingerprint. This live vascular fingerprint provides for ultrahigh security and a unique way for fingerprint-based personal verification. Because the system is based on blood flow, which only exists in a living person, the technique is robust against spoof attaching. After performing non-contact in-vivo imaging of a human fingertip, a three dimensional vasculature image is reconstructed from a plurality of vasculature tomography images and at least one vasculature fingerprint image which corresponds to the fingertip is extracted from the three dimensional vasculature image.

Abstract: Biometric authentication devices, systems and methods are provided. The authentication device includes biometric reader configured for generating raw biometric data indicative of a physiological characteristic of a user; and processor operatively coupled to the biometric reader, the processor being configured for: receiving the raw biometric data, generating derivative biometric data by processing a portion of the raw biometric data relating to a pre-selected aspect of the physiological characteristic, the pre-selected aspect being suitable for identifying the user, the derivative biometric data being indicative of a plurality of instances of the pre-selected aspect in the raw biometric data, generating biometric identification data from the derivative biometric data, the biometric identification data being based upon relationships between the plurality of instances of the pre-selected aspect in the raw biometric data, and using the biometric identification data to identify the user.

Abstract: A method and apparatus for applying gradient edge detection to detect features in a biometric, such as a fingerprint, based on data representing an image of at least a portion of the biometric. The image is modeled as a function of the features. Data representing an image of the biometric is acquired, and features of the biometric are modeled for at least two resolutions. The method and apparatus improves analysis of both high-resolution images of biometrics of friction ridge containing skin that include resolved pores and lower resolution images of biometrics without resolved pores.

Abstract: Real-time marker detection in medical imaging of a stent may be provided. A plurality of frames of image data may be obtained. A plurality of candidate markers for the stent may be determined in the plurality of frames of image data. One or more markers from the plurality of candidate markers may be detected. The detecting may be based on automatic initialization using a subset of frames of image data from the plurality of frames of image data. The detecting may be performed in real-time with the obtaining.

Abstract: A computer-implemented method of performing a combined surface reconstruction and registration of stereo laparoscopic images includes a computer system generating an intraoperative three-dimensional model of an anatomical area of interest and receiving a plurality of stereo endoscopic images of the anatomical area of interest from a laparoscope. The computer system performs a first stereo reconstruction process using the stereo endoscopic images to yield a first surface image corresponding to the anatomical area of interest and aligns the first surface image with a surface of the intraoperative three-dimensional model using a rigid registration process.

Abstract: A medical device comprises a processor programmed to detect and analyze perturbations of biologic particle densities and convert a set of features of the perturbations into a discreet set of quanta in relation to a phenotypic, baseline or expected range of the perturbation features. The processor is also programmed to convert at least a second set of features from a second perturbation into a second discreet set of quanta and to compare the first set of set of quanta with the second set of quanta and to render motion images of the perturbations and quanta. The quanta may be defined at least in part by the pattern of perturbations or a clinical condition.

Abstract: A system for presenting data to an image recognition system is described herein, wherein the system comprises at least one processor programmed to receive time specific medical data comprising a plurality of lab values, particle concentrations, and/or physical measurements of blood of a patient collected at a series of points in time and convert the biologic particle densities into image components, images or sequences of images. The processor is programmed to generate the image components, images or sequences of images on a map or display and to present the map or display to an image recognition system.

Abstract: A patient monitoring system detects perturbations and detects or determines features of the perturbations and generates image cells responsive to the perturbations, organelles within the cells responsive to the features, and clinical regions responsive to the cells, and visualizations responsive to the clinical regions. The system also generates time-lapsable motion images comprising the cells which change over time in response to changes in the features or the detection of new perturbations. The system may convert the features into quanta defined at least in part by the clinical condition and may generate image components, such as pixels or groups of pixels, responsive to the quanta. Motion images may be generated from the image components.

Abstract: The present invention discloses a method for extracting AIF and an application thereof to DCE-MRI. The method comprises steps: contacting a target tissue with a contrast agent to obtain a plurality of images; using the plurality of images to work out the tissue concentration curve of the contrast agent in each voxel; calculating the purity of the tissue concentration curve of each voxel according to the tissue concentration curves; and extracting the voxel having the highest purity as the optimized arterial location; and extracting the tissue concentration curve of the voxel having the highest purity as the arterial input function. The extracted AIF is applied to a pharmacokinetic model to obtain associated pharmacokinetic parameters. The present invention not only improves the accuracy and reliability of the derived quantitative indexes but also promotes the efficiency of the quantitative analysis.

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

Abstract: An apparatus and method are provided including a first segmenter and a second segmenter. The first segmenter is configured to generate a first segmentation result from a medical image using a first segmentation parameter for a candidate lesion. The second segmenter is configured to determine a target lesion to segment from among the candidate lesion based on the first segmentation result, and generate a second segmentation result using a second segmentation parameter to segment the target lesion.

Abstract: A medical image processing apparatus is configured as follows.

Abstract: A method of analyzing a medical image, where the medical image comprises one or more than one region of interest, and where the method comprises a) providing the medical image comprising a set of actual image values; b) rescaling the actual image values to produce corresponding rescaled image values and to produce a rescaled image from the rescaled image values; c) deriving a histogram of the rescaled image values; d) using the histogram to derive an adaptive segmentation threshold; e) using the adaptive segmentation threshold to recursively split the rescaled image; f) terminating the recursive splitting of the sub(sub) images using one or more than one predetermined criteria; and g) identifying one sub(sub) image in the terminated Hierarchical Region Splitting Tree which comprises the region of interest.

Abstract: A system and method is presented for assembling information contained within a financial instrument for subsequent verification of the financial instrument, wherein the financial instrument includes an identifier corresponding to a payee of the financial instrument. An imaging device, such as, for example, a mobile phone or the like, is used to obtain an image of the financial instrument prior to the financial instrument being transferred to the payee. Information is extracted from the image of the financial instrument, and the information is transferred to a storage area that is separate and remote from the imaging device.

Abstract: Generalized virtual inspectors are provided. One system includes two or more actual systems configured to perform one or more processes on specimen(s) while the specimen(s) are disposed within the actual systems. The system also includes one or more virtual systems coupled to the actual systems to thereby receive output generated by the actual systems and to send information to the actual systems. The virtual system(s) are configured to perform one or more functions using at least some of the output received from the actual systems. The virtual system(s) are not capable of having the specimen(s) disposed therein.

Abstract: A pattern inspection method includes acquiring an image of a pattern in a stripe region concerned, regarding each of stripe regions of the first group each not including an adjacent stripe region in plural stripe regions obtained by virtually dividing an inspection region of a target object on which patterns have been formed into the plural stripe regions each partially overlapping an adjacent stripe region, wherein the acquiring is performed using laser lights or electron beams, in a longitudinal direction of the stripe region of the first group, and acquiring an image of a pattern in a stripe region concerned, regarding each of stripe regions of the second group each not including an adjacent stripe region, in remaining stripe regions other than the first group stripe regions, wherein the acquiring is performed using laser lights or electron beams, in the longitudinal direction of the stripe region of the second group.

Abstract: Real-time stereo matching is described, for example, to find depths of objects in an environment from an image capture device capturing a stream of stereo images of the objects. For example, the depths may be used to control augmented reality, robotics, natural user interface technology, gaming and other applications. Streams of stereo images, or single stereo images, obtained with or without patterns of illumination projected onto the environment are processed using a parallel-processing unit to obtain depth maps. In various embodiments a parallel-processing unit propagates values related to depth in rows or columns of a disparity map in parallel. In examples, the values may be propagated according to a measure of similarity between two images of a stereo pair; propagation may be temporal between disparity maps of frames of a stream of stereo images and may be spatial within a left or right disparity map.

Abstract: An image processing apparatus is provided, which includes a first calculation unit to calculate a first position of at least one first point sampled from an actual 3-dimensional (3D) object to be acquired as stereo 3D images, a second calculation unit to calculate a second position of at least one second point of a receiving end corresponding to the first point, using at least one second parameter related to the receiving end provided with the stereo 3D images, and a determination unit to determine at least one first parameter related to a transmission end to acquire and provide the stereo 3D images to the receiving end so that a difference between the first position and the second position is minimized.

Abstract: An electronic device (100) includes a first processor (802) and a second processor (804) coupled to the first processor. The first processor (802) is to receive image data from a first imaging camera (114, 116) and to determine two-dimensional (2D) spatial feature data representing one or more 2D spatial features identified from the image data. The second processor (804) is to determine three-dimensional (3D) spatial feature data representing one or more 3D spatial features identified based on the 2D spatial feature data. Further, the first processor (802) can initiate detection of one or more 2D spatial features from a portion of an image frame prior to receiving the entire image frame.

Abstract: The spatial resolution of captured plenoptic images is enhanced. In one aspect, the plenoptic imaging process is modeled by a pupil image function (PIF), and a PIF inversion process is applied to the captured plenoptic image to produce a better resolution estimate of the object.

Abstract: A method for determining that a user associated with a first identifiable device or identifiable service is also associated with a second identifiable device or identifiable service by a) generating one or more first image descriptors for one or more first images stored on the first identifiable service associated with a first user, b) generating one or more second image descriptors for one or more second images stored on the second identifiable service associated with a second user, c) calculating, based on the generated first and second image descriptors, the probability that the first user is also the second user. Also provided is a computer readable storage medium containing program code for implementing the method.

Abstract: Camera or object pose calculation is described, for example, to relocalize a mobile camera (such as on a smart phone) in a known environment or to compute the pose of an object moving relative to a fixed camera. The pose information is useful for robotics, augmented reality, navigation and other applications. In various embodiments where camera pose is calculated, a trained machine learning system associates image elements from an image of a scene, with points in the scene's 3D world coordinate frame. In examples where the camera is fixed and the pose of an object is to be calculated, the trained machine learning system associates image elements from an image of the object with points in an object coordinate frame. In examples, the image elements may be noisy and incomplete and a pose inference engine calculates an accurate estimate of the pose.

Abstract: Examples disclosed herein relate to combining region based image classifiers. In one implementation, a processor measures correct classification and misclassification levels associated with a first image classifier related to a first image feature region and measures correct classification and misclassification levels associated with a second image classifier related to a second image feature region. The processor may create a combined classifier based on the first image classifier correct classification and misclassification levels and based on the second image classifier correct classification and misclassification levels such that the combined classifier is related to the first image feature region and the second image feature region.

Abstract: Provided are a method and apparatus for detecting an abnormal movement. The apparatus includes a feature tracing unit configured to extract features of a moving object in an input image, trace a variation in position of the extracted features according to time, and ascertain trajectories of the extracted features; a topic online learning unit configured to classify the input image in units of documents which are bundles of the trajectories, and ascertain probability distribution states of topics, which constitute the classified document, by using an online learning method which is a probabilistic topic model; and a movement pattern online learning unit configured to learn a velocity and a direction for each of the ascertained topics, and learn a movement pattern by inferring a spatiotemporal correlation between the ascertained topics.

Abstract: A method for estimating illumination of an image captured by a digital system is provided that includes computing a feature vector for the image, identifying at least one best reference illumination class for the image from a plurality of predetermined reference illumination classes using the feature vector, an illumination classifier, and predetermined classification parameters corresponding to each reference illumination class, and computing information for further processing of the image based on the at least one best reference illumination class, wherein the information is at least one selected from a group consisting of color temperature and white balance gains.

Abstract: A method of generating user insights based on one or more user images and one or more other data is provided, including receiving one or more image files on an identifiable device or service, receiving at least one of image metadata or identifiable device or service metadata, analyzing features of the received image files, based on at least one of the received image metadata or identifiable device or service metadata and generating at least one user insight for a user associated with the identifiable device or service. Also provided is a computer readable storage medium containing program code for implementing the method.

Abstract: An invention is disclosed for classifying a graphic—e.g. as text or non-text. In embodiments, machine learning is used to generate a solution for classifying graphics of a graphic based on providing the machine learning system a plurality of graphics that are already classified. The way to determine a classification is then used by a remote presentation session server to classify tiles of frames to be transmitted to a client in a remote presentation session. The server encodes the tiles based on their classifications and transmits the encoded tiles to the client.

Abstract: Systems and methods for object detection by receiving an image; segmenting the image and identifying candidate bounding boxes which may contain an object; for each candidate bounding box, dividing the box into overlapped small patches, and extracting dense features from the patches; during a training phase, applying a learning process to learn one or more discriminative classification models to classify negative boxes and positive boxes; and during an operational phase, for a new box generated from the image, applying the learned classification model to classify whether the box contains an object.

Abstract: Various aspects of a system and method for image processing may include a computing device having one or more processors. The computing device may be operable to determine luminance values of multiple pixels in a subset of a frame of a two-dimensional image. The computing device may be operable to determine texture values of the multiple pixels in the subset of the frame. The computing device may be operable to identify a subject region and a background region in the frame of the two-dimensional image based on the determined luminance values and the determined texture values of the plurality of pixels.

Abstract: According to an aspect of the present invention, an image processing method for extracting a pixel having a specific feature includes: extracting pixels representing an object, to which the pixel having the specific feature belongs, from a given input image based on an image feature other than color; extracting principal colors from the pixels; selecting, from a plurality of pre-trained color distribution models deposited in a repository, a color distribution model closest in distance metric, which indicates distance relative to the extracted principal colors, to the extracted principal colors by performing a search through the repository using the extracted principal colors; and segmenting the input image by categorizing pixels in the input image using the selected color distribution model.

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: According to one embodiment, an environment evaluation apparatus includes a generation unit, a storage and a comparison unit. The generation unit generates a feeling index representing a feeling toward a target image to be processed. The storage stores a plurality of comparative images and corresponding comparative feeling indexes, according to each of feeling categories. The comparison unit extracts, as a similar image, at least one of the comparative images corresponding to at least one of the comparative feeling indexes having a degree of similarity to the feeling index not less than a threshold value, by comparing the feeling index with the comparative feeling indexes.

Abstract: A method is disclosed. The method includes analyzing each tile of a sheetside image to determine if one or more color values of a tile exceeds a predetermined maximum value.

Abstract: The techniques introduced here include a system and method for transcoding multimedia content based on the results of content analysis. The determination of specific transcoding parameters, used for transcoding multimedia content, can be performed by utilizing the results of content analysis of the multimedia content. One of the results of the content analysis is the determination of image type of any images included in the multimedia content. The content analysis uses one or more of several techniques, including analyzing content metadata, examining colors of contiguous pixels in the content, using histogram analysis, using compression distortion analysis, analyzing image edges, or examining user provided inputs. Transcoding the multimedia content can include adapting the content to the constraints in delivery and display, processing and storage of user computing devices.

Abstract: An encoder may implement an indexed color history that stores color values for previously encoded pixels. The encoder may obtain a current pixel or current group of pixels for encoding and determine whether to encode the current pixel using the indexed color history. In doing so, the encoder may compare a color value of the current pixel with color values of the previously coded pixels to determine whether the current pixel is sufficiently similar to a previously coded pixel color value, e.g., by satisfying one or more similarity criteria. When the similarity criteria are satisfied, the encoder may encode the current pixel as an index value referencing the entry in the indexed color history storing a color value that satisfies the similarity criteria. When the similarity criteria are not satisfied, the encoder may encode the current pixel using another encoding method or technique.

Abstract: A computer-implemented method of acquiring tax data for use in tax preparation application includes acquiring an image of at least one document containing tax data therein with an imaging device. A computer extracts one or more features from the acquired image of the at least one document and compares the extracted one or more features to a database containing a plurality of different tax forms. The database may include a textual database and/or geometric database. The computer identifies a tax form corresponding to the at least one document from the plurality of different tax forms based at least in part on a confidence level associated with the comparison of the extracted one or more features to the database. At least a portion of the tax data from the acquired image is transferred into corresponding fields of the tax preparation application.

Abstract: Disclosed is an imaging apparatus for generating data of a phase image based on an interference pattern acquired by a shearing interferometer, including: a differential phase data calculating unit that calculates first differential phase data expressing a change of a phase in a first direction and second differential phase data expressing a change of a phase in a second direction, based on interference pattern data generated by an electromagnetic wave transmitted through a subject; a second-order differential phase data calculating unit that calculates first second-order differential phase data by differentiating the first differential phase data in the first direction, and calculates second second-order differential phase data by differentiating the second differential phase data in the second direction; and a phase data calculating unit that calculates the phase image by solving a second-order differential equation including the first and second second-order differential phase data as functions.

Abstract: In accordance with various aspects of the disclosure, a detecting engine for detecting targets/materials in hyperspectral scenes is disclosed. The detecting engine combines data partitioning and dimensionality reduction to reduce the number of computations needed to identify in which pixels in a hyperspectral scene a given material is present. Computation reduction (in some instances, by two fold) greatly impacts the speed of and power consumed by the detecting engine making the engine suitable for hyperspectral imaging of large scenes, processing using many filters per pixel, or missions requiring testing large numbers of reference spectra to see which are present in a scene.

Abstract: Systems and methods are provided for creating contour images that represent the contour of objects reflected in images, calculating contour histogram descriptors of the contour images, and classifying images based in part on the histogram descriptors of the contour images. For example, a contour image of an image is created. A radial-polar grid having a plurality of radial-polar bins is then positioned on the contour image. A contour histogram descriptor is created to include a number of bins that correspond to the radial-polar bins of the radial-polar grid, where the contents of the bins of the contour histogram descriptor represent the number of pixels of the contour image that are located in the corresponding radial-polar bins of the radial-polar grid. Images are classified at least based in part on comparisons between contour histogram descriptors of the images and contour histogram descriptors of training images.

Abstract: A method and/or system for screenshot orientation detection may include performing an initial optical character recognition (OCR) and/or an initial face recognition technique on a screenshot of an application. A determination of whether the screenshot orientation is correct may be made based on, for example, the initial OCR and/or the initial face recognition technique. In an event when the screenshot orientation is not correct, a determination of a correct screenshot orientation may be made. In this regard, the screenshot may be rotated (e.g., by a predetermined number of degrees). A subsequent OCR and/or a subsequent face recognition technique may be performed on the rotated screenshot. A determination may be made whether the screenshot orientation of the rotated screenshot is correct based on, for example, the subsequent OCR and/or the subsequent face recognition technique.

Abstract: A system and method for removing noise from images are disclosed herein. An exemplary system includes an edge-detection-based adaptive filter that identifies edge pixels and non-edge pixels in an image and selects a filtering technique for at least one non-edge pixel based on a comparison of the at least one non-edge pixel to a neighboring pixel region, wherein such comparison indicates whether the at least one non-edge pixel is a result of low-light noise.

Abstract: An apparatus for estimating a disparity map based on at least two images is provided. The apparatus includes at least two processing units, which include a pixel recursion unit configured to determine a disparity value as a pixel recursion disparity candidate based on a plurality of pixel values of the at least two images and a selector configured to select a selected disparity candidate to determine at least one of the disparity map values of the disparity map. The selector is adapted to select the selected disparity candidate from a candidate group assigned to the selector. The candidate group assigned to the selector includes the pixel recursion disparity candidate, a second disparity candidate and a third disparity candidate. Moreover, the selector is adapted to select the selected disparity candidate independently from a different selector of a different processing unit of the at least two processing units.

Abstract: An illustrative mobile device includes a data storage configured to at least temporarily store visual information and at least one processor that is configured to determine whether to request visual information processing from a network with which the mobile device may communicate. The processor is configured to determine a mobile device condition and a network condition. The processor determines a type of feature from the visual information to use for classification based on the determined mobile device and network conditions. The processor is configured to classify the visual information based on the determined type of feature and determine a confidence indicator based on the classification. The processor determines whether to request visual information processing from the network based on the determined confidence indicator.

Abstract: The classification and segmentation system of the current invention makes use of information from pixels of an image, namely the magnitude of the pixels, to run specific analytics to classify and segment the image pixels into different groups. This invention includes a system for processing an image, the system including an input device, a processor, a memory and a monitor. The input device is configured to receive image data, where the image data includes pixels and each pixel has a magnitude. The memory has instructions stored in it that, when executed by the processor, cause the processor to run calculations. The calculations include: calculating the log-magnitudes from the magnitudes of at least a plurality of the pixels, calculating standard deviations of the log-magnitudes for subsets of the plurality of pixels and compute an integral of the standard deviations over a desired range. The pixels are classified into different groups based on a value of the integral relative to one or more integral values.

Abstract: A method is disclosed. The method includes retrieving one or more compressed objects and inserting the compressed objects directly into a compressed bitmap during compression of a sheetside image.

Abstract: Disclosed are a method and an apparatus for image encoding/decoding. The method for image decoding includes comparing whether a size of a current transform block and a size of a smallest transform block (smallest transform unit (STU)) are the same as each other, and decoding information indicating whether transformation is performed on the current transform block and determining whether to perform inverse transformation on the current transform block based on the decoded information indicating whether the transformation is performed when the size of the current transform block and the size of a smallest transform block are the same as each other.

Abstract: A system for enhancing an input image including receiving an input image and filtering the input image with a plurality of non-linear smoothing filters providing a respective plurality of filtered outputs. The system processes a plurality of the filtered outputs with respect to at least one of another of the filtered outputs and the input image to determine a plurality of detail layers. The system filters the plurality of detail layers with a plurality of non-linear smoothing filters providing a respective plurality of smoothed layers. The system adjusts the plurality of smoothed layers in such a manner that regions closer to an edge are enhanced to a lesser extent than regions farther from an edge and combining the adjusted the smoothed layers to provide an enhanced output image.

Abstract: A method of processing a digital image. The method comprises: populating (100) a bilateral grid (10) comprising a plurality of cells (20), based on information obtained from the image, each cell comprising at least one value; then cumulatively integrating (110) the at least one value over the bilateral grid to form an integrated grid comprising integrated values; generating (120) a modified bilateral grid, comprising computing the sum of the at least one value over a predetermined rectangular box of cells of the bilateral grid, by using the integrated values corresponding to the corners of the box; and slicing (130) the modified bilateral grid to generate an output image.

Abstract: A depth noise filtering method and apparatus is provided. The depth noise filtering method may perform spatial filtering or temporal filtering according to depth information. In order to perform spatial filtering, the depth noise filtering method may determine a characteristic of a spatial filter based on depth information. Also, in order to perform temporal filtering, the depth noise filtering method may determine a number of reference frames based on depth information. The depth noise filtering method may adaptively remove depth noise according to depth information and thereby enhance a noise filtering performance.

Abstract: Provided is an image processing apparatus including an edge identifying portion that generates an edge image in which an edge is identified at each pixel in an input image; a mask-image generating portion that distinguishes an edge direction at a pixel of interest in the input image, that calculates a difference between pixel values of pixels that are positioned perpendicular to the edge direction and that are positioned symmetrically to each other, with the pixel of interest located at a center thereof, and that generates a mask image in which a pixel value of the pixel of interest is increased as that difference decreases; an enhancement-filter image generating portion that generates an enhancement-filter image by multiplying pixel values of pixels of the edge image by pixel values of the mask image; and a combining portion that generates an output image by combining the input image and the enhancement-filter image.