Abstract: Discerning small, weak features (“specks”) from imagery can be critical in early-stage cancer detection and other applications. In one aspect, the presence of a speck is judged from a large set of “votes” about whether a point in the imagery has a value above or below its neighbors. Hundreds or thousands or more votes can be gathered from one or more images, to thereby—in the aggregate—tend to confirm or refute the presence of a speck at a particular location. Votes can be based on simple pixel differences, e.g., between a pixel at the center of a 7×7 pixel image excerpt, and each of 48 other pixels in the excerpt. More sophisticated methods can employ analyses of triads, quads, and rings, and kernel-based Markov Random Field frameworks, to roll-up to a final conclusion. A great number of other features and arrangements are also detailed. The technology is particularly illustrated in the context of detecting exoplanets from astronomical imagery of remote star systems.

Abstract: There is provided an image processing device including a detection unit configured to detect a mask from an acquired image, a determination unit configured to determine whether there is a change in the mask detected by the detection unit, and an output unit configured to output a parameter when the determination unit determines that there is a change in the mask, the parameter being related to the mask detected by the detection unit before it is determined that there is a change in the mask.

Abstract: An image encoding apparatus includes a calculation unit configured to calculate a profile indicating a combination of processes which can be decoded by an image decoding apparatus and a level indicating a range of a parameter value which can be decoded by the image decoding apparatus, a determination unit configured to determine a number of horizontal pixels of a tile or a number of horizontal tiles with respect to a specific profile to be N or smaller (N>0) which is a maximum number of horizontal pixels defined in advance according to the level, and to determine a number of vertical pixels of the tile or a number of vertical tiles with respect to the specific profile to be M or smaller (M>0) which is a maximum number of vertical pixels defined in advance according to the level.

Abstract: A system for, and method of, extracting a surface profile from a stereo pair of images obtained at an arbitrary setting S of an optical system, includes determining surface profile reconstruction parameters for images obtained with the optical system at a reference setting So of the optical system; determining warping parameters for a digital image processor for warping images obtained with the optical system at the arbitrary setting S into images corresponding to the reference setting So; obtaining the stereo pair of images from at least one camera of the optical system; warping the stereo pair of images into images corresponding to the reference setting So, and using the surface profile reconstruction parameters to determine the surface profile. In a particular embodiment, the surface profile is passed to a computer model of tissue deformation and used to determine an intra-surgery location of a tumor or other anatomic feature of tissue.

Abstract: A method for static and moving object detection employing a motion computation method based on spatio-temporal tensor formulation, a foreground and background modeling method, and a multi-cue appearance comparison method. The invention operates in the presence of shadows, illumination changes, dynamic background, and both stopped and removed objects.

Abstract: Systems and techniques for refined row guidance parameterization with Hough transform are described herein. An electronic representation of a field (ERF) can be received. A steering variable calculation can be performed by executing a cascaded Hough transform on the ERF. An intermediate value used in calculating the steering variable can be selected. A refined intermediate value can be identified from the intermediate value by measuring a difference between the intermediate value and an anchor value. The steering variable calculation can be adjusted using the refined intermediate value.

Abstract: Methods, apparatuses, systems, and software for extended phase correction in phase sensitive Magnetic Resonance Imaging. A magnetic resonance image or images may be loaded into a memory. Two vector images A and B associated with the loaded image or images may be calculated either explicitly or implicitly so that a vector orientation by one of the two vector images at a pixel is substantially determined by a background or error phase at the pixel, and the vector orientation at the pixel by the other vector image is substantially different from that determined by the background or error phase at the pixel. A sequenced region growing phase correction algorithm may be applied to the vector images A and B to construct a new vector image V so that a vector orientation of V at each pixel is substantially determined by the background or error phase at the pixel.

Abstract: There is provided a measurement apparatus including an objective lens, a stage, a setting unit, and a controller. The stage is configured to support a sample vessel in which a plurality of wells each containing a sample are arranged and to define relative positions of the sample vessel and the objective lens. The setting unit is configured to determine whether to set each of the plurality of wells to be a measurement target and set the measurement target. The controller is configured to control the stage such that a well determined to be the measurement target by the setting unit and the objective lens face each other.

Abstract: The present invention relates to a method to process a three dimensional seismic image. The method comprises, for a center point and for a plane comprising said center point, determining a first maximal correlation between a first vector of the seismic values associated with at least a point of the seismic image having a distance to the center point below the predetermined distance and on a first line, and a second vector of the seismic values associated with points on a second line parallel to the first line, determining a second maximal correlation between the first vector, and a third vector of the seismic values associated with points on a third line parallel to the first line, and determining a difference value based on at least a difference between the first maximal correlation and the second maximal correlation.

Abstract: A method of detecting a dynamic weather event includes the steps of: (a) receiving video images of a scene from a camera; (b) dividing each of the video images into multiple regions, in which a region is defined by a range of distances from the camera to objects in the scene; (c) selecting a region; and (d) segmenting the selected region into a plurality of three-dimensional (3D) image patches, in which each 3D image patch includes a time-sequence of T patches, with each patch comprised of N×M pixels, wherein N, M and T are integer numbers. The method also includes the following steps: measuring an image intensity level in each of the 3D image patches; masking 3D image patches containing image intensity levels that are above a first threshold level, or below a second threshold level; and extracting features in each 3D image patch that is not discarded by the masking step. Based on the extracted features, the method makes a binary decision on detecting a dynamic weather event.

Abstract: A method for reconstructing an image of a subject with a medical imaging system, such as a magnetic resonance imaging system, is provided. Medical image data is acquired from the subject with the medical imaging system, and one or more images of the subject are reconstructed from the medical image data while constraining the one or more images to be consistent with a signal model that relates image intensity values in the image to a free parameter that is associated with a physical property of the subject. The signal model may be an analytical signal model or an approximate signal model learned from acquired medical image data. The model consistency condition may be enforced using an operator that projects an image estimate onto the space of all functions satisfying the signal model.

Abstract: A method and apparatus for image processing includes receiving images, detecting non-stationary objects in the images, displaying a first image that includes a non-stationary object, selecting a frame region including the non-stationary object in the first image, selecting a second image based on a low similarity with the first image, and replacing image data in the frame region of the first image with image data represented in the frame region of the second image.

Abstract: Embodiments of the invention are directed to a computer-implemented system and method of identifying human settlements in imagery comprising receiving an image, segmenting the image into a plurality of superpixels, analyzing statistical parameters of at least two or more of the plurality of superpixels, where the statistical parameters includes entropy data, and identifying groups of superpixels having at least a predetermined cluster density and a predetermined entropy. Some embodiments further include clipping the image to only include the identified groups of superpixels having the predetermined cluster density and entropy, analyzing statistical parameters of the clipped image, analyzing geometric factors of the clipped image, determining one or more settlements based on the statistical parameters and geometric factors of the superpixels, and identifying a shape and area of the one or more settlements based on the statistical parameters and geometric factors of the clipped image.

Abstract: The present invention relates to the field of computation and simulation and covers methods to optimize the fiducial marker positions in optical object tracking systems, by simulating the visibility.

Abstract: A filtering device includes an evaluation value deriving module that derives, for a pair of generated images having mutual relevance, multiple evaluation values indicative of correlations between any one of blocks extracted from one of the images and multiple blocks extracted from the other image, respectively, a reference waveform part setting module that sets a reference waveform part of a transition waveform comprised of the multiple evaluation values, the reference waveform part containing the evaluation value having the highest correlation, and a difference value determining module that determines whether one or more similar waveform parts similar to the reference waveform part exist in the transition waveform, and determines, based on the result of the determination, whether the evaluation value with the highest correlation is valid as a difference value.

Abstract: To provide an object detection device and an object detection method in which incorrect grouping based on a range image can be prevented, processing is implemented including: generating a range image based on a pair of gray-scaled images (S603); grouping adjacent regions having range data representing close distances in the range image (S604); calculating differences between the luminance values of pixels in a vertical line below a ground plane above which objects are imaged and the luminance values of pixels in a vertical line above the ground plane in the gray-scaled images and dividing the group region into laterally separated sub-regions (S605); and determining whether or not there is a section without vertical edge in either of the left and right areas of each of sub-regions made based on the gray-scaled images and merging sub-regions whose areas including a section without vertical edge are next to each other (S607).

Abstract: Various embodiments utilize two-dimensional (“2D”) and three-dimensional (“3D”) object features for purposes such as object recognition and/or image matching. For example, a user can capture an image (e.g., still images or video) of an object and can receive information about items that are determined to match the object. For example, the image can be analyzed to detect visual features (e.g., corners, edges, etc.) of the object and the detected visual features can be combined to generate a combined visual feature vector which can be used for object recognition, image matching, or other such purposes. Other approaches utilize the image to generate a 3D model of the object represented in the image, which can be used to determine at least one object or types of objects that match the object represented in the image.

Abstract: Implementations generally relate to optimizing a photo album layout. In some implementations, a method includes receiving a plurality of images and determining a target arrangement. The method also includes arranging the plurality of images in an N-dimensional arrangement based on a predetermined distance function. The method also includes arranging the plurality of images in the target arrangement based on the N-dimensional arrangement.

Abstract: An object identification system comprises an optical code reader that scans an optical code of an object and decodes a portion of the optical code. Using the decoded portion of the optical code, a database filter unit generates a filtered subset of feature models from a set of feature models of known objects stored in a database. An image capture device captures an image of the object, and a feature detector unit detects visual features in the image. A comparison unit compares the detected visual features to the filtered subset of feature models to identify a match between the object and a known object.

Abstract: A medical article and m-number of first local features which are respectively constituted by a feature vector of 1 dimension to i dimensions of m-number of feature points in an image of the medical article are stored in association with each other, n-number of feature points are extracted from an image in a captured video, n-number of second local features respectively constituted by a feature vector of 1 dimension to j dimensions are generated, a smaller number of dimensions among the number of dimensions i and the number of dimensions j is selected, and an existence of the medical article in the image in the video is recognized when it is determined that a prescribed ratio or more of the m-number of first local features up to the selected number of dimensions corresponds to the n-number of second local features up to the selected number of dimensions.