Abstract: A method of segmenting a digital image of biological tissue includes accessing a ranking model calculated from training data representing shapes of conforming and non-conforming biological unit exemplars. The ranking model may include support vectors defining a hyperplane in a vector space. The method further includes accessing image data representing the digital image, identifying a first shape and a set of second constituent shapes in the digital image, wherein the first shape comprises a union of the set of second constituent shapes, determining a rank of a first data point in the image data corresponding to the first shape and a rank of a second data point in the image data corresponding to the set of second constituent shapes into the vector space, and segmenting the digital image using the first shape or the set of second constituent shapes based on which data point has a greater respective rank.

Abstract: Systems and methods for extracting information about an organism of interest, such as an atlas of the organism of interest; a storage device for at least temporarily storing an image of the organism of interest; and an operating device that automatically creates a map of the image of the organism of interest and automatically compares the map of the image to the atlas of the organism.

Abstract: In accordance with one aspect of the present technique, a method is disclosed. The method includes receiving a new video from one or more sensors and generating a new content graph (CG) based on the new video. The method also includes comparing the new CG with a plurality of prior CGs. The method further includes identifying a first portion of the new CG matching a portion of a first prior CG and a second portion of the new CG matching a portion of the second prior CG. The method further includes analyzing a first set of semantic annotations (SAs) associated with the portion of the first prior CG and a second set of SAs associated with the portion of the second prior CG. The method further includes generating a sequence of SAs for the new video based on the analysis of the first and the second set of SAs.

Abstract: Embodiments of the disclosure are directed to segmenting a digital image of biological tissue into biological units, such as cells. A first weak or data driven segmentation is generated using image data representing the digital image to segment the digital image into a first set of biological units. Applying a geometric model, each unit in the first set of biological units is ranked based on a similarity in shape and scale between the unit and one or more other units in the image. A subset of units from the first set of biological units is selected based on the rank of each biological unit relative to a predetermined threshold rank. A second weak or data driven segmentation may then be generated using image data including the subset of biological units to segment that portion of the digital image into a second set of biological units.

Abstract: This invention, which provides a method for detecting a corruption in an image acquired from a biological sample, includes: providing at least one image of at least one cell; generating the image of the at least one cell over a period of time; determining if the at least one image of the at least one cell is corrupted; applying a wavelet transform, Fourier transform, or other frequency decomposing transform to the at least one image to decompose the at least one image into a plurality of sub-images, wherein the plurality of sub-images have a plurality of low frequency channels, a plurality of middle frequency channels and a plurality of high frequency channels; calculating a ratio based on an energy level of the plurality of low frequency channels and the plurality of middle frequency channels; and removing the at least one image of at least one cell if the at least one image is corrupted.

Abstract: Exemplary embodiments include methods, systems, and devices for enabling users to provide quality scores for indicating the quality of image analysis methods performed on images of biological tissue. An exemplary user interface displays results of an image analysis method performed on an image of biological tissue in an overlaid manner on an image of biological tissue. The exemplary user interface enable a user to provide, directly on the user interface, one or more quality scores to indicate the user's assessment of the quality of the image analysis performed on the image. Exemplary embodiments store the quality scores provided by the user in association with the image analysis method and the image of biological tissue.

Abstract: The present invention is directed to method and system for image processing of test wells on a microplates wherein the microplates' test well wall boundaries are identified through the use of a candidate edge image wherein the candidate edge image represents locations of one or more segments of the wall boundaries.

Abstract: A device and method for processing an image to create appearance and shape labeled images of a person or object captured within the image. The appearance and shape labeled images are unique properties of the person or object and can be used to re-identify the person or object in subsequent images. The appearance labeled image is an aggregate of pre-stored appearance labels that are assigned to image segments of the image based on calculated appearance attributes of each image segment. The shape labeled image is an aggregate of pre-stored shape labels that are assigned to image segments of the image based on calculated shape attributes of each image segment. An identifying descriptor of the person or object can be computed based on both the appearance labeled image and the shape labeled image. The descriptor can be compared with other descriptors of later captured images to re-identify a person or object.

Abstract: A device and method for processing an image to create appearance and shape labeled images of a person or object captured within the image. The appearance and shape labeled images are unique properties of the person or object and can be used to re-identify the person or object in subsequent images. The appearance labeled image is an aggregate of pre-stored appearance labels that are assigned to image segments of the image based on calculated appearance attributes of each image segment. The shape labeled image is an aggregate of pre-stored shape labels that are assigned to image segments of the image based on calculated shape attributes of each image segment. An identifying descriptor of the person or object can be computed based on both the appearance labeled image and the shape labeled image. The descriptor can be compared with other descriptors of later captured images to re-identify a person or object.

Abstract: Aspects of the disclosure provide a method for crowd segmentation that can globally optimize crowd segmentation of an input image based on local information of the input image. The method can include receiving an input image of a site, initializing a plurality of hypothesis based on the input image, dividing the input image into a plurality of patches, calculating an affinity measure of one or more patches to a hypothesis based on a partial response of the patches to a whole body classifier of the hypothesis that includes a combination of weak classifiers, and optimizing assignments of the plurality of patches to the plurality of hypothesis based on the affinity measures of the plurality of patches to the plurality of hypothesis.

Abstract: The subject matter disclosed herein relates to X-ray imaging systems, and more specifically to digital X-ray imaging systems. In one embodiment, an imaging system includes an X-ray source configured to emit X-rays. The imaging system also includes an X-ray detector configured to detect the emitted X-rays and produce a corresponding electrical signal. The imaging system also includes a gantry configured to at least partially revolve the X-ray source and the X-ray detector about a primary rotational axis. The X-ray detector is coupled to the gantry so that a diagonal of the X-ray detector is oriented substantially perpendicular to the primary rotational axis.

Abstract: A device and method for detecting targets of interest in an image, such as people or objects of a certain type. Targets are detected based on an optimized strong classifier descriptor that can be based on a combination of weak classifier descriptors. The weak classifier descriptors can include a user-defined weak classifier descriptor that is defined by a user to represent a shape or appearance attribute that is characteristic of parts of the target of interest. The strong classifier descriptor can be optimized by selecting a subset of weak classifier descriptors that exhibit improved performance in detecting targets in training images.

Abstract: The present invention aims at providing a method for detecting a color of a signal light from a moving vehicle such as railroad train. The method includes capturing an image from a camera mounted on the moving vehicle and extracting candidate regions in the image that contain light region. The method further includes classifying the candidate regions as a signal light region or a non-signal light region and identifying the color of the signal light region.

Abstract: A device and method for processing an image to create appearance and shape labeled images of a person or object captured within the image. The appearance and shape labeled images are unique properties of the person or object and can be used to re-identify the person or object in subsequent images. The appearance labeled image is an aggregate of pre-stored appearance labels that are assigned to image segments of the image based on calculated appearance attributes of each image segment. The shape labeled image is an aggregate of pre-stored shape labels that are assigned to image segments of the image based on calculated shape attributes of each image segment. An identifying descriptor of the person or object can be computed based on both the appearance labeled image and the shape labeled image. The descriptor can be compared with other descriptors of later captured images to re-identify a person or object.

Abstract: A device and method for processing an image to create appearance and shape labeled images of a person or object captured within the image. The appearance and shape labeled images are unique properties of the person or object and can be used to re-identify the person or object in subsequent images. The appearance labeled image is an aggregate of pre-stored appearance labels that are assigned to image segments of the image based on calculated appearance attributes of each image segment. The shape labeled image is an aggregate of pre-stored shape labels that are assigned to image segments of the image based on calculated shape attributes of each image segment. An identifying descriptor of the person or object can be computed based on both the appearance labeled image and the shape labeled image. The descriptor can be compared with other descriptors of later captured images to re-identify a person or object.

Abstract: A device and method for efficient computation of statistical information, such as a mean, co-variance, or histogram of the image pixels, over discrete image regions. The computation employs integral computations to determine the statistical information over image regions of arbitrary shape, including irregular polygonal shaped regions. The integral computations are simplified by categorizing corner points of boundaries of image regions. The computation can be applied to calculate descriptors or signatures of persons or objects within an image. The computation also has a low computational cost enabling fast calculation of image statistics.

Abstract: A device and method for processing an image to create appearance and shape labeled images of a person or object captured within the image. The appearance and shape labeled images are unique properties of the person or object and can be used to re-identify the person or object in subsequent images. The appearance labeled image is an aggregate of pre-stored appearance labels that are assigned to image segments of the image based on calculated appearance attributes of each image segment. The shape labeled image is an aggregate of pre-stored shape labels that are assigned to image segments of the image based on calculated shape attributes of each image segment. An identifying descriptor of the person or object can be computed based on both the appearance labeled image and the shape labeled image. The descriptor can be compared with other descriptors of later captured images to re-identify a person or object.

Abstract: A method and system for distributed tracking of multiple targets is disclosed. Multiple targets to be tracked by a plurality of trackers are detected in a frame. The motion state variable of each of the plurality of trackers is calculated in the E-step of a variational Expectation-Maximization algorithm. Further, the data association variable of each of the plurality of trackers is calculated in the M-step of the algorithm. Depending on the motion state variable and the data association variable, the multiple targets are tracked.

Abstract: The present invention is directed to method and system for image processing of test wells on a microplates wherein the microplates' test well wall boundaries are identified through the use of a candidate edge image wherein the candidate edge image represents locations of one or more segments of the wall boundaries.

Abstract: The present techniques provide for the evaluation of cellular motion and/or cellular properties based on an analysis of motion. In an exemplary technique, images of one or more cells are acquired and motion data for the one or more cells is derived from the images. The motion data is decomposed to generate one or more motion components. The one or more motion components can be used to evaluate cellular properties and/or cellular motion properties.