Abstract: An embodiment of the present disclosure provides a method of generating a tomography image and an X-ray imaging apparatus operating according to the method, whereby when a material with a high X-ray attenuation rate is inserted into an object, an image quality may be improved by reducing ripple artifacts and/or undershoot artifacts that may occur in a tomography image that is a captured X-ray image of the object.

Abstract: A method for characterizing polarization image information and a method for computing characterization parameters are provided. The method includes: obtaining n polarized subimages of a polarization imaging target, wherein each polarized subimage corresponds to a different polarization angle and n?3; and computing a parameter matrix [ILP (x, y) INLP(x, y) ?(x, y)] of a polarization cosine characterization equation of all pixel points of the polarization imaging target according to all polarized subimages and the polarization cosine characterization equation of the polarization imaging target. The disclosure obtains a maximum polarization intensity image and a minimum polarization intensity image through computing multiple polarization intensity images, which improves the accuracy of polarization imaging, and the degree of accuracy is much higher than macroscopic accuracy.

Abstract: Systems and methods are disclosed for image signal processing. For example, methods may include receiving a first image from a first image sensor; receiving a second image from a second image sensor; determining an electronic rolling shutter correction mapping for the first image and the second image; determining a parallax correction mapping based on the first image and the second image for stitching the first image and the second image; determining a warp mapping based on the parallax correction mapping and the electronic rolling shutter correction mapping, wherein the warp mapping applies the electronic rolling shutter correction mapping after the parallax correction mapping; applying the warp mapping to image data based on the first image and the second image to obtain a composite image; and storing, displaying, or transmitting an output image that is based on the composite image.

Abstract: A medical image processing apparatus includes processing circuitry configured to receive first volume data and second volume data; set a first symmetry plane for the first volume data and a second symmetry plane for the second volume data; and conduct a registration of the first volume data and the second volume data based on the first symmetry plane and the second symmetry plane.

Abstract: A technology capable of estimating information on a position and a size of a pupil or an iris using an image obtained by photographing eyes of a subject even when a part of the pupil or the iris is hidden in the image is provided.

Abstract: A vision inspection system includes a sorting platform having an upper surface supporting parts for inspection. An inspection station is positioned adjacent the sorting platform including an imaging device to image the parts in a field of view. A vision inspection controller receives images from the imaging device. The vision inspection controller includes an image histogram tool to pre-process the images to improve contrast of the images by redistributing lightness values of the images based on adaptive histogram equalization processing to generate enhanced images. The vision inspection controller processes the enhanced images based on an image analysis model to determine inspection results for each of the parts. The vision inspection controller has an artificial intelligence learning module operated to customize and configure the image analysis model based on the enhanced images.

Abstract: A method for generating an high-dynamic-range (HDR) color image from a dual-exposure-time single-shot HDR color image sensor includes obtaining pixel values generated by a local region of sensor pixels of the image sensor, determining a motion parameter for the local region from pixel values associated with a first color, and demosaicing the pixel values of the local region to determine, for each of three colors, an output value of the images pixel, wherein relative contributions of short-exposure-time pixels and long-exposure-time pixels to the output value are weighted according to the motion parameter.

Abstract: An audio acquisition device positioning method is provided. In the method, a first image that includes an audio acquisition device is obtained. The audio acquisition device in the first image is identified. First coordinate data of the identified audio acquisition device in the first image is obtained. First displacement data is determined according to the first coordinate data and historical coordinate data of the audio acquisition device. First coordinates of the audio acquisition device are determined according to the first displacement data.

Abstract: A computer-implemented system and method of image cross-correlation improves the sub-pixel accuracy of the correlation surface and subsequent processing thereof. One or both of the template or search windows are resampled using the fractional portions of the correlation offsets X and Y produced by the initial image cross-correlation. The resampled window is then correlated with the other original window to produce a resampled cross-correlation surface. Removing the fractional or sub-pixel offsets between the template and search windows improves the “sameness” of the represented imagery thereby improving the quality and accuracy of the correlation surface, which in turn improves the quality and accuracy of the FOM or other processing of the correlation surface. The process may be iterated to improve accuracy or modified to generate resampled cross-correlation surfaces for multiple possible offsets and to accept the one with the most certainty.

Abstract: Techniques for integrating sensor data into a scene or map based on statistical data of captured environmental data are discussed herein. The data may be stored as a multi-resolution voxel space and the techniques may comprise first applying a pre-alignment or localization technique prior to fully integrating the sensor data.

Abstract: A learning device, an image generating device, a learning method, an image generating method, and a program are provided which can improve accuracy of estimation of an environment outside an angle of view of an image input to an image generating section. A second learning data obtaining section (64) obtains an input image. A second learning section (66) obtains result data indicating a result of execution of semantic segmentation on the input image. An input data generating section (38) generates input data obtained by coupling the input image and the result data to each other. By using the input data as input, the second learning section (66) performs learning of a wide view angle image generating section (28) that generates, in response to input of data obtained by coupling an image to a result of execution of semantic segmentation on the image, an image having a wider angle of view than the image.

Abstract: A tracking device includes a processor including hardware, and the processor sets a start frame, extracts multiple representative points of a contour of a tracking target, tracks the extracted multiple representative points, performs outlier determination based on an interrelationship of the tracked multiple representative points, performs a process of removing an outlier representative point determined to be an outlier, and extracts new representative points based on multiple representative points after the process of removing the outlier representative point when a given condition is met.

Abstract: A projection device and a projection picture correction method thereof are provided. When the projection device performs projection toward a projection surface, a plurality of target coordinates of a plurality of target vertexes are obtained based on a plurality of planes of the projection surface. The plurality of planes are not coplanar with each other, and the plurality of target vertexes form a target polygon. A first direction scaling process is performed respectively on a plurality of first image portions of an original trapezoidal image and a trapezoidal image block is generated. A second direction scaling process is performed respectively on a plurality of second image portions of the trapezoidal image block and a target image block aligned with the target polygon is generated. An output image including the target image block is projected onto the projection surface.

Abstract: An integrated navigation solution is provided for a device within a moving platform. Motion sensor data from a sensor assembly of the device is obtained, optical samples from at least one optical sensor for the platform are obtained and map information for an environment encompassing the platform is obtained. Correspondingly, an integrated navigation solution is generated based at least in part on the obtained motion sensor data using a nonlinear state estimation technique, wherein the nonlinear state estimation technique uses a nonlinear measurement model for optical sensor data. Generating the integrated navigation solution includes using the sensor data with the nonlinear state estimation technique and integrating the optical sensor data directly by updating the nonlinear state estimation technique using the nonlinear measurement model and the map information. The integrated navigation solution is then provided.

Abstract: Embodiments of this disclosure include a method and an apparatus for processing image. The method may include obtaining a to-be-processed image and performing image semantic segmentation on the to-be-processed image to obtain a semantically-segmented image. The semantically-segmented image may include a target region and a non-target region obtained through the semantic segmentation. The method may further include performing pose recognition on the to-be-processed image, to obtain a pose-recognized image recognizing skeletal region. The method may further include fusing the target region and the non-target region of the semantically-segmented image with the skeletal region of the pose-recognized image, to obtain a trimap comprising foreground region, background region, and recognition region. The method may further include generating, according to the to-be-processed image and the trimap, a transparency mask image for separating image from the to-be-processed image.

Abstract: An object tracking device includes a storage unit that stores in advance a reference for a movement amount of an object between frames for each position or area on a fisheye image, a determining unit that determines, based on a position of the object in a first frame image and the reference for a movement amount associated with the position of the object in the first frame image, a position of a search area in a second frame image subsequent to the first frame image, and a search unit that searches the search area in the second frame image for the object to specify a position of the object in the second frame image.

Abstract: An individual identification apparatus that identifies an individual product having a pattern of irregularities randomly formed on a surface thereof includes an imaging unit and an extracting unit. The imaging unit is configured to acquire an image obtained by capturing a date mark formed on the product. The extracting unit is configured to extract a feature value related to the pattern of the irregularities from the image as data identifying the individual product.

Abstract: A method includes obtaining at least one image and a ground truth map associated with the at least one image. The method also includes generating multiple optical maps using multiple algorithms and the at least one image. The method further includes, for each algorithm, identifying at least one score for the algorithm using one or more of the optical maps generated using the algorithm and the ground truth map. The ground truth map identifies one or more boundaries associated with one or more foreground objects in the at least one image. The scores identify how well the optical maps generated using the algorithms separate the one or more foreground objects from a background in the at least one image.

Abstract: An apparatus includes a first acquisition unit that acquires a plurality of likelihood maps by setting a plurality of different weight parameters in a trained model that outputs, with an image feature extracted from the input image as an input, a likelihood map including, in association with a position in the input image, a likelihood indicating a possibility that the object is present, and a detection unit that detects, based on the acquired plurality of the likelihood maps, the position of the object included in the input image, wherein the trained model is a model that has learned the weight parameters based on loss values at least acquired using a first loss function for reducing a likelihood around a position of interest in the likelihood map, and a second loss function for increasing a likelihood acquired at the position of the object in the input image.

Abstract: A technology is described for spatially estimating thermal emissivity. A method can include obtaining spectral emissivity data and satellite imaging data for a geographic area. A weighted emissivity model of emissivity values may be generated for surfaces included in the geographic area from the spectral emissivity data and the satellite imaging data, wherein the spectral emissivity data is mapped to the satellite imaging data to generate the weighted emissivity model. Thermal imaging data for the geographic area may be received from an airborne thermal imaging sensor and a thermal emissivity map can be generated for the geographic area using the thermal imaging data and the weighted emissivity model. The emissivity values from the weighted emissivity model can be used to estimate thermal emissivity values.