Abstract: A method is provided for automatic identification of the contours of at least one portion of a predefined bone on the basis of a plurality of images representing parallel sections through a measurement volume including the portion of bone and which are obtained by a medical imaging technique. The method includes: a step of obtaining at least one shape of closed contour in at least one of the filtered images; a step of associating with each of the shapes a tag selected within a predefined bone-related nomenclature; a step of classifying the shapes so as to form at least one group of shapes delimiting a common volume isolated in space; a step of selecting the shapes of the group of target shapes.

Abstract: A trajectory estimation apparatus includes: an image acceptance unit which accepts images that are temporally sequential and included in the video; a hierarchical subregion generating unit which generates subregions at hierarchical levels by performing hierarchical segmentation on each of the images accepted by the image acceptance unit such that, among subregions belonging to hierarchical levels different from each other, a spatially larger subregion includes spatially smaller subregions; and a representative trajectory estimation unit which estimates, as a representative trajectory, a trajectory, in the video, of a subregion included in a certain image, by searching for a subregion that is most similar to the subregion included in the certain image, across hierarchical levels in an image different from the certain image.

Abstract: A system may receive image data and capture motion with respect to a target in a physical space and recognize a gesture from the captured motion. It may be desirable to isolate aspects of captured motion to differentiate random and extraneous motions. For example, a gesture may comprise motion of a user's right arm, and it may be desirable to isolate the motion of the user's right arm and exclude an interpretation of any other motion. Thus, the isolated aspect may be the focus of the received data for gesture recognition. Alternately, the isolated aspects may be an aspect of the captured motion that is removed from consideration when identifying a gesture from the captured motion. For example, gesture filters may be modified to correspond to the user's natural lean to eliminate the effect the lean has on the registry of a motion with a gesture filter.

Abstract: Systems and methods for tracking human hands by performing parts based template matching using images captured from multiple viewpoints are described. One embodiment of the invention includes a processor, a reference camera, an alternate view camera, and memory containing: a hand tracking application; and a plurality of edge feature templates that are rotated and scaled versions of a finger template that includes an edge features template. In addition, the hand tracking application configures the processor to: detect at least one candidate finger in a reference frame, where each candidate finger is a grouping of pixels identified by searching the reference frame for a grouping of pixels that have image gradient orientations that match one of the plurality of edge feature templates; and verify the correct detection of a candidate finger in the reference frame by locating a grouping of pixels in an alternate view frame that correspond to the candidate finger.

Abstract: A computer-implemented method for use in assessing a cornea which includes selecting a principal image from among a series of layered images of the cornea. The computer-implemented method further includes detecting a plurality of corneal structures in the principal image and providing a quantitative analysis of the plurality of corneal structures.

Abstract: A circuit includes an image decompression circuit configured to receive compressed image data which are generated by compressing image data of a set of pixels of a target block by using a selected compression method selected from a plurality of compression methods based on a correlation among said image data of said set of pixels of said target block, and to generate decompressed image data by decompressing said compressed image data by using a decompression method corresponding to said selected compression method.

Abstract: An object detection apparatus includes an image acquisition unit that acquires image data, a reading unit that reads the acquired image data in a predetermined image area at predetermined resolution, an object area detection unit that detects an object area from first image data read by the reading unit, an object discrimination unit that discriminates a predetermined object from the object area detected by the object area detection unit, and a determination unit that determines an image area and resolution used to read second image data which is captured later than the first image data from the object area detected by the object area detection unit, wherein the reading unit reads the second image data from the image area at the resolution determined by the determination unit.

Abstract: An image processing apparatus includes a moving image input unit configured to input a moving image, an object likelihood information storage unit configured to store object likelihood information in association with a corresponding position in an image for each object size in each frame included in the moving image, a determination unit configured to determine a pattern clipping position where a pattern is clipped out based on the object likelihood information stored in the object likelihood information storage unit, and an object detection unit configured to detect an object in an image based on the object likelihood information of the pattern clipped out at the pattern clipping position determined by the determination unit.

Abstract: The present invention relates to an imaging system for imaging a region of interest, wherein the imaging system comprises a projection data generation unit including a radiation source (2) and a detection unit (6) for acquiring projection data in different angular directions. The projection generation unit is adapted for acquiring projection data in an acquisition region on the detection unit. The imaging system further comprises a reconstruction unit (12) for reconstructing a first image of the region of interest from the acquired projection data and a forward projection unit (13) for forward projecting through the first image of the region of interest for calculating projection data corresponding to regions on the detection unit outside of the acquisition region. The reconstruction unit (12) is adapted for reconstructing a second image of the region of interest from the acquired projection data and from the calculated projection data.

Abstract: A system and method for assessing the operation of a imaging system, such as magnetic resonance imaging (MRI) system, is disclosed including a that computer is programmed to access an image of a phantom from image data, identify a plurality of seed point in the image of the phantom using a shape recognition algorithm, and rank combinations of the seed points using a pattern recognition algorithm using a priori information about the predefined pattern. The computer is programmed to rank the combinations of the seed points to generate an indication of an imaging quality characteristic of the imaging system.

Abstract: An object tracking apparatus is provided that enables the possibility of erroneous tracking to be further reduced.

Abstract: A method for processing XYZ point cloud of a scene acquired by a GmAPD LADAR includes: performing on a computing device a three-dimensional statistical differencing on the XYZ point cloud obtained from the GmAPD LADAR to produce a SD point cloud; and displaying an image of the SD point cloud.

Abstract: A system and method for creating 3-dimensional agricultural field scene maps are disclosed comprising producing a pair of images using a stereo camera and creating a disparity image based on the pair of images, the disparity image being a 3-dimensional representation of the stereo images. Coordinate arrays can be produced from the disparity image and the coordinate arrays can be used to render a 3-dimensional local map of the agricultural field scene. Global maps can also be made by using geographic location information associated with various local maps to fuse together multiple local maps into a 3-dimensional global representation of the field scene. The disparity images can be used to analyze a variety of agricultural features.

Abstract: A system and method for tracking, identifying, and labeling objects or features of interest is provided. In some embodiments, tracking is accomplished using unique signature of the feature of interest and image stabilization techniques. According to some aspects a frame of reference using predetermined markers is defined and updated based on a change in location of the markers and/or specific signature information. Individual objects or features within the frame may also be tracked and identified. Objects may be tracked by comparing two still images, determining a change in position of an object between the still images, calculating a movement vector of the object, and using the movement vector to update the location of an image device.

Abstract: A marker placement device includes, a marker placement method decision section that decides, for every predetermined pitch from a starting edge of a side to an end edge of the side, a placement position of a marker for detecting a position within a rectangular image region, the placement position being along the side of the image region within an image. A marker adding section that adds the marker to the image according to the placement position decided is provided, where, when a gap shorter than the pitch remains between the end edge and the decided placement position closest to the end edge of the side, the marker placement method decision section decides a first marker placement position closest to the starting edge, and decides a subsequent marker placement position.

Abstract: A system and method for tracking, identifying, and labeling objects or features of interest is provided. In some embodiments, tracking is accomplished using unique signature of the feature of interest and image stabilization techniques. According to some aspects a frame of reference using predetermined markers is defined and updated based on a change in location of the markers and/or specific signature information. Individual objects or features within the frame may also be tracked and identified. Objects may be tracked by comparing two still images, determining a change in position of an object between the still images, calculating a movement vector of the object, and using the movement vector to update the location of an image device.

Abstract: In an object tracking device, a search region setting unit sets the search region of an object in a frame image at a present point in time, based on an object region in a frame image at a previous point in time, zoom center coordinates in the frame image at the previous point in time, and a ratio between the zoom scaling factor of the frame image at the previous point in time and the zoom scaling factor of the frame image at the present point in time. A normalizing unit normalizes the image of a search region of the object included in the frame image at the present point in time to a fixed size. A matching unit searches the normalized mage of the search region for an object region similar to a template image.

Abstract: Automated quantitative analysis of microcirculation, such as density of blood vessels and red blood cell velocity, is implemented using image processing and machine learning techniques. Detection and quantification of the microvasculature is determined from images obtained through intravital microscopy. The results of quantitatively monitoring and assessing the changes that occur in microcirculation during resuscitation period assist physicians in making diagnostically and therapeutically important decisions such as determination of the degree of illness as well as the effectiveness of the resuscitation process. Advanced digital image processing methods are applied to provide quantitative assessment of video signals for detection and characterization of the microvasculature (capillaries, venules, and arterioles).

Abstract: Mobile phones and other portable devices are equipped with a variety of technologies by which existing functionality can be improved, and new functionality can be provided. Some aspects relate to visual search capabilities, and determining appropriate actions responsive to different image inputs. Others relate to processing of image data. Still others concern metadata generation, processing, and representation. Yet others concern user interface improvements. Other aspects relate to imaging architectures, in which a mobile phone's image sensor is one in a chain of stages that successively act on packetized instructions/data, to capture and later process imagery. Still other aspects relate to distribution of processing tasks between the mobile device and remote resources (“the cloud”). Elemental image processing (e.g., simple filtering and edge detection) can be performed on the mobile phone, while other operations can be referred out to remote service providers.

Abstract: A method and a system for calculating a time to go value between a vehicle and an intruding object. A first image of the intruding object at a first point of time retrieved. A second image of the intruding object at a second point of time is retrieved. The first image and the second image are filtered so that the first image and the second image become independent of absolute signal energy and so that edges become enhanced. An X fractional pixel position and a Y fractional pixel position are set to zero. The X fractional pixel position denotes a horizontal displacement at sub pixel level and the Y fractional pixel position denotes a vertical displacement at sub pixel level. A scale factor is selected. The second image is scaled with the scale factor and resampled to the X fractional pixel position and the Y fractional pixel position, which results in a resampled scaled image.