Abstract: A method for increasing enhancing local contrast in a thermal image for a class of objects having a thermal characteristic is provided. The method including providing thermal image data representing a first thermal image, where the first thermal image is acquired by an absolute calibrated thermal imaging system, redistributing the thermal image data having a first intensity distribution into a second intensity distribution using a predetermined redistribution function, where the predetermined redistribution function is based on the thermal characteristic, such that the local contrast is enhanced for the class of objects, outputting the redistributed thermal image data as the thermal image. An apparatus for enhancing local contrast in a thermal image for a class of objects having a thermal characteristic is further provided.

Abstract: A method for face recognition in the video comprises: performing feature extraction on a target face in multiple image frames in the video to generate multiple face feature vectors respectively corresponding to the target face in the multiple image frames; performing time sequence feature extraction on the plurality of face feature vectors to convert the plurality of face feature vectors into a feature vector of a predetermined dimension; and judging the feature vector of the predetermined dimension by using a classifier so as to recognize the target face.

Abstract: Method and system for obtaining images of an object of interest using a system comprising an x-ray source facing a detector. The method and system enable the acquiring of a plurality of 2D projection images of the object of interest in a plurality of orientations. A selected 2D projection image such as the zero projection of the plurality of projections can be enhanced by using at least a subset of the plurality of tomosynthesis projection images. The obtained enhanced 2D projection image is displayed for review.

Abstract: A biological image processing device includes: a memory; and a processor coupled to the memory and the processor configured to execute a process, the process comprising: extracting at least one line from contours of a palm and principal lines of the palm shown in an image of the palm; extracting pixels of the line extracted by the extracting of at least one line; setting a local region for each of the pixels, each local region including each corresponding one of the pixels; calculating, for each local region, local orientations of the line extracted by the extracting of at least one line, in accordance with gradient intensities related to respective orientations of each corresponding local region; and calculating an orientation of the palm in accordance with a statistical amount of the respective local orientations.

Abstract: The invention provides a method of processing an image in a diagnostic apparatus of diagnosing a cutaneous lesion using a cutaneous image, comprising the steps of: (a) obtaining a first detail image made by performing a first component separation filter on a brightness component of the cutaneous image; (b) obtaining a second detail image made by performing a second component separation filter on the brightness component of the cutaneous image, the second component separation filter having properties different from those of the first component separation filter; (c) generating a third detail image based on the first detail image and the second detail image; (d) newly generating a third base image based on the third detail image; and (e) combining the third detail image with the third base image to restore a brightness component and generate a highlighted image.

Abstract: A facial recognition apparatus comprises a photographing parameter input unit that receives a photographing parameter(s); a lighting information estimation unit that estimates lighting information based on the photographing parameter(s); and a recognition accuracy control unit that controls a recognition accuracy parameter(s) based on the lighting information.

Abstract: An information processing apparatus includes an image acquisition unit, variation amount deriving unit, acquisition unit, and threshold value deriving unit. The image acquisition unit acquires a captured image obtained by an imaging unit. The variation amount deriving unit derives a luminance value variation amount of a predetermined area of the acquired captured image based on a luminance value of the predetermined area and first information indicating a relationship between a captured image luminance value and an amount of luminance value variation. The acquisition unit acquires an amount of variation of a luminance gradient value based on the derived amount of variation of the luminance value, wherein the luminance gradient value is a gradient value of the luminance value. The threshold value deriving unit derives a threshold value with which an obtained luminance gradient value is to be compared, based on the acquired amount of variation of the luminance gradient value.

Abstract: A method photo-based positioning includes obtaining a positioning photo taken by a mobile device within a predetermined space; comparing multiple feature elements exacted from sampling photos taken within the predetermined space in advance with the positioning photo to determine each feature element existing in the positioning photo; obtaining a first position coordinate of each feature element which is determined to exist in the positioning photo in a sampling photo corresponding to the positioning photo, and a second position coordinate of each feature element which is determined to exist in the positioning photo in the positioning photo; and calculating position parameters of the mobile device by using each of the obtained first position coordinate and second position coordinate, wherein the least number of feature elements existing in the positioning photo is determined according to the number of the position parameters.

Abstract: A method in a computing device for quantitative surgical image registration includes: prior to a surgical procedure, obtaining, using a first imaging modality, a preoperative image of patient tissue and a plurality of preoperative measurements of a material property of the patient tissue. The preoperative measurements correspond to respective points in the preoperative image. The method includes storing the preoperative image and the preoperative measurements, and during the surgical procedure, using a second imaging modality, capturing an intraoperative image of the patient tissue and a second plurality of intraoperative measurements of the material property of the patient tissue. The intraoperative measurements correspond to respective points in the intraoperative image.

Abstract: A structured illumination microscope device includes acquisition unit that repeats a series of processing steps including controlling a combination of a wave vector and phase of fringes and acquiring N images; and computing unit in which processing for demodulating the image of the sample using a required M types of images from an image set of consecutive P images. The M types of images include: Q types (where Q?3) of modulated images; and one type of modulated image having the wave vector in common with and the phase differing from at least one among the Q types of modulated images, or one unmodulated image. An arrangement of the N images satisfies the uniformity condition, meaning “intensity distribution of the fringes is spatially uniform when accumulated between the N images” and the refresh condition, meaning “the M types of images are always included in the image set”.

Abstract: A biometric information process device includes: an image device configured to capture an image of an object; a memory; and a processor coupled to the memory and the processor configured to execute a process, the process comprising: detecting a touch point of the object with respect to a touch panel; extracting a biometric feature from the image of the object that is acquired by the image device; and correcting biometric information acquired from the image of the object based on a movement amount of the object on the touch panel and a movement amount of the biometric feature in the image of the object when the touch point detected in the detecting moves.

Abstract: A method and system for detecting a fall risk condition, the system comprising a surveillance camera configured to generate a plurality of frames showing an area in which a patient at risk of falling is being monitored, and a computer system comprising memory and logic circuitry configured to store motion feature patterns that are extracted from video recordings, the motion feature patterns are representative of motion associated with real alarm cases and false-alarm cases of fall events, receive a fall alert from a classifier, determine motion features of one or more frames from the plurality of frames that correspond to the fall alert; compare the motion features of the one or more frames with the motion feature patterns, and determine whether to confirm the fall alert based on the comparison.

Abstract: Methods and systems detect changes occurring over time between synthetic aperture sonar (SAS) images. A processor performs coarse navigational alignment, fine-scale co-registration and local co-registration between current image data and historical image data. Local co-registration includes obtaining correlation peaks for large neighborhood non-overlapping patches. Relative patch translations are estimated and parameterized into error vectors. Interpolation functions formed from the vectors re-map the current image onto the same grid as the historical image and the complex correlation coefficient between images is calculated. The resulting interferogram is decomposed into surge and sway functions used to define the argument of a phase function, which is multiplied by the current image to remove the effects of surge and sway on the interferogram. Based on the aforementioned computations, a canonical correlation analysis is performed to detect scene changes between the historical and new SAS images.

Abstract: Systems and methods of generating a compact visual vocabulary are provided. Descriptor sets related to digital representations of objects are obtained, clustered and partitioned into cells of a descriptor space, and a representative descriptor and index are associated with each cell. Generated visual vocabularies could be stored in client-side devices and used to obtain content information related to objects of interest that are captured.

Abstract: A method for operating a scanning microscope and for determining point spread functions, with which sample images are recorded with the scanning microscope. The method includes scanning a sample with at least one illuminating light beam; recording at least one sample image with a detector device during a scan by the illuminating light beam; and comprising the point spread function, with which a sample image is recorded, from the at least one sample image. A detector device having receiving elements is used, where the distance between the receiving elements is smaller than a diffraction disk that generates a sample point on the detector device. Detector signals, generated by means of the receiving elements, are read out for each of the different positions of the illuminating light beam on the sample, as a result of which the scanning of the sample allows the detector signals, which are read out, to generate a plurality of sample images.

Abstract: According to examples of the presently disclosed subject an active triangulation system includes an active triangulation setup and a calibration module. The active triangulation setup includes a projector and a sensor. The projector is configured to project a structured light pattern that includes a repeating structure of a plurality of unique feature types and a plurality of markers distributed in the projected structured light pattern, where an epipolar distance between any two epipolar lines which are associated with an appearance in the image of any two respective markers is greater than a distance between any two distinguishable epipolar lines. The sensor is configured to capture an image of a reflected portion of the projected structured light. The calibration module is configured to determine an epipolar field for the active triangulation setup according to locations of the markers in the image, and to calibrate the active triangulation setup.

Abstract: A method and apparatus for detecting an object using an event-based sensor is provided. An object detection method includes determining a feature vector based on target pixels and neighbor pixels included in an event image, and determining a target object corresponding to the target pixels based on the feature vector.

Abstract: The invention provides a retinal prosthetic method and device that mimics the responses of the retina to a broad range of stimuli, including natural stimuli. Ganglion cell firing patterns are generated in response to a stimulus using a set of encoders, interfaces, and transducers, where each transducer targets a single cell or a small number of cells. The conversion occurs on the same time scale as that carried out by the normal retina. In addition, aspects of the invention may be used with robotic or other mechanical devices, where processing of visual information is required. The encoders may be adjusted over time with aging or the progression of a disease.

Abstract: An image processing method includes at least the following steps: partitioning a picture into a plurality of slices, wherein each slice row in the picture includes at least one slice; generating a compressed picture by encoding each of the slices; and controlling at least one of start of transmission of encoded data of a slice row and end of the transmission of encoded data of the slice row according to a transmission synchronization event.

Abstract: A resolution estimating device is achieved which is capable of adequately estimating the resolution of the original image of any received image signal. A resolution estimating device (1000) includes a proximity-degree acquiring unit (1), an accumulation unit (2), a frequency transform unit (3), and a spectrum analyzing unit (4). The proximity-degree acquiring unit (1) acquires the proximity degree value of each target pixel. The accumulation unit (2) accumulates the proximity degrees of the target pixels, for example, in the vertical direction on the image, and obtains a one-dimensional data sequence of the accumulated proximity degree values. The frequency transform unit (3) performs a frequency transform on the one-dimensional data sequence of the accumulated proximity degree values obtained by the accumulation unit (2), and obtains a one-dimensional frequency-component data sequence which is a one-dimensional data sequence for frequency regions.