Abstract: According to an embodiment, a 2-dimensional (2-D) image of a geographical region is transformed via a regional maxima transform (RMT) or an edge segmenting and boundary filling (ESBF) transform to produce a filtered 2-D image. The filtered 2-D image is iteratively eroded and opened to produce a processed EO 2-D image, 2-D object shape morphology is extracted from the processed EO 2-D image, and 2-D shape properties are extracted from the 2-D object shape morphology. A height slice of a 3-dimensional (3-D) point cloud comprising 3-D coordinate and intensity measurements of the geographical region is generated, and slice object shape morphology is extracted from the height slice. Slice shape properties from the slice object shape morphology are extracted, and the 2-D image is constellation matched to the height slice based on the 2-D shape properties and the slice shape properties.

Abstract: A method for vision machine inspection comprises providing depth information of a target acquired by an image capturing system, determining real-time three-dimensional information of a target object in a predetermined inspecting area based on depth information of at least one real-time image of the target. The method further comprises projecting color pixel information of a real-time color image of the target object to a three-dimensional virtual model based on the real-time three-dimensional information. The real-time color image may be acquired by a color camera system. The method further comprises generating a color three-dimensional virtual model. The color three-dimensional virtual model may comprise the color pixel information.

Abstract: Systems and methods are provided for selecting feature points within an image. A plurality of candidate feature points are identified in the image. A plurality of feature points are selected for each of the plurality of candidate feature points, a plurality of sets of representative pixels. For each set of representative pixels, a representative value is determined as one of a maximum chromaticity value and a minimum chromaticity value from the set of representative pixels. A score is determined for each candidate feature point from the representative values for the plurality of sets of representative pixels associated with the candidate feature point. The feature points are selected according to the determined scores for the plurality of candidate feature points.

Abstract: An image processing apparatus performs positioning between a plurality of spectral band images obtained by capturing images inside a lumen using a plurality of rays of light having wavelength bands different from one another. The image processing apparatus includes: a spectral band image acquisition unit configured to acquire the spectral band images; a spatial frequency component extraction unit configured to extract feature data for each spatial frequency band from each pixel in at least one spectral band image of the spectral band images; a weight calculation unit configured to calculate weights for each spatial frequency band given to the at least one spectral band image, based on the feature data for each spatial frequency band extracted from each pixel in the at least one spectral band image; and a positioning unit configured to perform positioning between the spectral band images based on the weights for each spatial frequency band.

Abstract: The location of a face is detected from data about a scene. A 3D surface model from is obtained from measurements of the scene. A 2D angle data image is generated from the 3D surface model. The angle data image is generated for a virtual lighting direction, the image representing angles between a ray directions from a virtual light source direction and normal to the 3D surface. A 2D face location algorithm is applied to each of the respective 2D images. In an embodiment respective 2D angle data images for a plurality of virtual lighting directions are generated and face locations detected from the respective 2D images are fused.

Abstract: The present invention provides a method and apparatus for encoding applications in an image. One embodiment of the method includes forming a first image that encodes information indicative of a map relating one or more pixel patterns to functionality implemented by a processor-based device. The first image is formed so that the processor-based device can decode the information to generate the map. The method also includes forming a second image that includes the pixel pattern(s). The second image is formed so that the processor-based device can detect the pixel pattern(s) and implement the functionality using the map.

Abstract: Special displays of medical images are generated that help a radiologist better detect nodules by exploiting the inherent human visualization abilities of detection of symmetry, asymmetry, motion and relative motion. A Region of Interest (ROI) on an x-ray (mammogram, CT-scan, MRI, or other medical image) is selected and the data within the ROI is copied such that a new display now has two or more copies of the information within the ROI. This copy may contain the same relative positions as the original image, or may be a mirror image of the original data. The ROI is moved over the medical image in search of nodules. This movement can be random, under the direct control of the radiologist, systematically moved by a computer algorithm, or some combination of the above.

Abstract: With an image processing device, a presence/absence of a product defect is judged based on detected-image data obtained by a radiographic device that detects radiation that has passed through a product, which is an inspection subject. With the image processing device, a position of a product feature in the detected-image data is identified based on a shape of the product feature indicated by feature data stored in a storage portion in advance, defect candidates are extracted with reference to the identified product feature in the detected-image data, and the presence/absence of a product defect is judged based on characteristic quantities of product defects indicated by a defect characteristic stored in the storage portion in advance and characteristic quantities of the defect candidates.

Abstract: A computer-implemented method for determining magnetic field inversion time of a tissue species includes generating a T1-mapping image of a tissue of interest, the T1-mapping image comprising a plurality of T1 values within an expected range of T1 values for the tissue of interest. An image mask is created based on predetermined identification information about the tissue of interest. Next, an updated image mask is created based on a largest connected region in the image mask. The updated image mask is applied to the T1-mapping image to yield a masked image. Then, a mean relaxation time value is determined for the largest connected region. The mean relaxation time value is then used to determine a time point for nulling longitudinal magnetization.

Abstract: A method generates a high-resolution (HR) image from a low-resolution (LR) image using regression functions. During a training stage, training HR images are downsampled to LR images. A signature is determined for each LR-HR patch pair based on a local ternary pattern (LTP). The signature is a low dimensional descriptor used as an abstraction of the patch pair features. Then, patch pairs with the same signature are clustered, and a regression function which maps the LR patches to the HR patches is determined. In some cases patch pairs of similar signatures can be combined for learning and a single regression function determined, thus decreasing the number of required regression functions. During actual upscaling, LR patches of an input image are similarly processed to obtain the signatures and from the regression functions. The LR patches can then be upscaled using the training regression functions.

Abstract: Refraction angles in a planet's atmosphere are mapped using a database of known star locations and a field imager onboard a platform above the planet. The field imager is positioned to observe a region that includes a portion of the planet's atmospheric limb. A star field image is captured for the region. The star field image includes stars within the field imager's field-of-view. Using the field imager and the database, a modeled star field image is generated that is matched in size to the field-of-view associated with the star field image. The modeled star field image defines absolute locations of stars corresponding to stars appearing in the field imager's field-of-view. Differences between the absolute locations and locations of the images of stars are indicative of a limb refraction angle field.

Abstract: A spherical harmonic is defined which is an operationally optimal small finite subset of the infinite number of spherical harmonics allowed to exist mathematically. The composition of the subset differs depending on its position on virtual hemisphere. The subsets are further divided into small spherical tesserae whose dimensions vary depending on the distance from the hemispherical center. The images of the outside visual scenes are projected on the flat surface of the webcam and from there are read and recalculated programmatically as if the images have been projected on the hemisphere. rotational invariants are then computed in the smallest tesserae using numerical integration, and then invariants from neighboring tesserae are added to compute the rotational invariant of their union. Every computed invariant is checked with the library and stored there if there is no match. The rotational invariants are solely used for visual recognition and classification and operational decision making.

Abstract: An optical sensing device can receive a speckle pattern generated by a laser's interaction with acoustically stimulated tissue. A computing device can identify one or more characteristics within the received speckle pattern. The computing device can then identify a match of the one or more characteristics to a user biometric signature stored within a storage device. Based upon the identified match, the system can authenticate a user within a computer system.

Abstract: The present invention provides, in at least one aspect, methods and systems that detect at least one face in at least one digital image, determine and store area co-ordinates of a location of the at least one detected face in the at least one digital image, apply at least one transformation to the at least one detected face to create at least one portrait of the at least one detected face, rotate the at least one portrait at least until the at least one portrait is shown in a vertical orientation and a pair of eyes of the at least one face shown in the at least one portrait are positioned on a horizontal plane; and store the rotated at least one portrait.

Abstract: An information processing apparatus includes an irradiation unit to irradiate a measurement target with a measurement pattern for distance measurement. An imaging unit obtains a captured image including the irradiated measurement target. A first detection unit detects first and second regions from the captured image. The first region includes a first portion of the measurement target that reflects a greater amount of light toward the imaging unit. The second region includes a second portion of the measurement target that reflects a lesser amount of light toward the imaging unit. A second detection unit detects, from the measurement pattern, a first region with which the first portion is irradiated and a second region with which the second portion is irradiated. A generation unit generates a measurement pattern that has different amounts of irradiation light depending on regions. A distance to the measurement target is derived using an obtained captured image.

Abstract: A method for defect classification includes storing, in a computer system, a definition of a region in a feature space. The definition is associated with a class of defects and comprises a kernel function comprising a parameter. The parameter determines a shape of the region. A confidence threshold for automatic classification of at least one defect associated with the class is received. A value of the parameter associated with the confidence threshold is selected. Inspection data for a plurality of defects detected in one or more samples under inspection is received. The plurality of defects for the class are automatically classified using the kernel function and the selected value of the parameter.

Abstract: The present invention provides a method for obtaining a human-face feature vector from a video image sequence, comprising: detecting a same human-face image in a plurality of image frames of the video sequence; dividing the detected human-face image into a plurality of local patches with a predetermined size, wherein each local patch is around or near a human-face feature point; determining a correspondence relationship between respective local patches of the same human-face image in the plurality of image frames of the video sequence; and using human-face local feature vector components extracted from respective local patches having a mutual correspondence relationship to form human-face local feature vectors representing facial points corresponding to the local patches. Besides, the present invention further provides an apparatus for obtaining a human-face feature vector from a video image sequence and a corresponding computer program product.

Abstract: A method for reconstructing an image of a subject from multi-coil data acquired with an array of radio frequency (“RF”) receiver coils that form a part of a magnetic resonance imaging (“MRI”) system without the need for coil sensitivity calibration is provided. A coil data set is acquired for each of the RF receiver coils, for example, by undersampling k-space. A set of image blocks that defines the location and size of each of a plurality of image blocks in the image domain is then selected. The acquired coil data sets and selected image block set are then used to jointly estimate a coil image for each of the plurality of RF receiver coils while promoting locally-low rank structure in the coil images. These coil images are then combined to produce the target image of the subject.

Abstract: For digital pathology imaging, intelligent processing, such as automatic recognition or content-based retrieval, is one significant benefit that drives the wide application of this technology. Before any intelligent processing on pathology images, every image is converted into a feature vector which quantitatively capture its visual characteristics. An algorithm characterizing pathology images with statistical analysis of local responses of neural networks is described herein. The algorithm framework enables extracting sophisticated textural features that are well adapted to the image data of interest.

Abstract: In an example embodiment, may be embodied in a a data analysis apparatus comprises a control unit configured to provide data representative of a three dimensional image, the three dimensional image including at least a three dimensional coordinate space which includes at least one plane that divides the three dimensional coordinate space into at least two regions, a display unit configured to produce the three dimensional image based on the data representative of the three dimensional image, and an input unit configured to provide data representative of at least one of a movement and a position of the at least one plane. In other example embodiments, the present disclosure may be embodied in a data analysis server, a data analysis system, and/or a computer readable medium.