Abstract: A method of price text detection by an imaging controller comprises obtaining, by the imaging controller, an image of a shelf supporting labels bearing price text, generating, by the imaging controller, a plurality of text regions containing candidate text elements from the image, assigning, by the imaging controller, a classification to each of the text regions, selected from a price text classification and a non-price text classification. The imaging controller, within each of a subset of the text regions having the price text classification: detects a price text sub-region and generates a price text string by applying character recognition to the price text sub-region. The method further includes presenting, by the imaging controller, the locations of the subset of text regions, in association with the corresponding price text strings.

Abstract: An image processing method for identifying text on production line components obtains an image to be recognized and a standard image for reference and extracts a first text area of the image to be recognized. A second text area of the standard image is obtained, and a text window is extracted based on the second text area. The method further obtains a target text area of the image to be recognized based on the first text area and the text window, and obtains a first set of first text sub-areas, and obtains a second set of second text sub-areas, by dividing the second text area into sub-windows of the text window. The method further marks the image to be recognized as a qualifying image when each first text sub-area of the first set is the same as a corresponding second text sub-area of the second set.

Abstract: The method is for dividing dark objects, substructures and background of an image from an electron microscope into segments by analyzing pixel values. The segments are transformed and aligned so that the transformed objects, sub-structures and background are meaningfully comparable. The transformed segments are clustered into classes which are used for ontological investigation of samples that are visualized by using electron microscopy. A triangle inequality comparison can be used to further cluster groups of objects to transfer understanding from different interactions between objects and to associate interactions with each other.

Abstract: An example electronic system is described in which an imaging device includes a lens and an image sensor. The imaging device is aligned with an optical target. The optical target includes a text character of a defined text size. An image capturer activates the imaging device to capture an electronic image of the optical target. The electronic image includes the text character of the optical target. An optical recognizer generates an optical recognition result for the character based on the captured electronic image. A sharpness detector compares the optical recognition result with a true value of the text character included in the optical target. Based on the comparison, a designated or defined text size is selected as a designated resolution. The designated resolution is then associable with the imaging device, the optical target, the electronic image, or a component thereof.

Abstract: The present invention relates to a device and a control method therefor and, more specifically, the device comprises: a memory for storing at least one command; a depth camera for capturing at least one hand of a user; a display module; and a controller for controlling the memory, the depth camera, and the display module. The controller controls the depth camera so as to capture the at least one hand of a user and controls the display module so as to output a visual feedback that changes on the basis of the captured hand of a user.

Abstract: Systems and methods that facilitate determining interaction between medications and the brain using a brain measure and a brain model. Hidden nervous system states are difficult to predict, diagnose, and treat with therapeutic medications. A Dual Neural Machine Translation (d-NMT) algorithmic system that utilizes sets of parameters for a relapsing-remitting MS model based on patient medical records and adjusts a method of parameterization to produce a model that can match patients' medical records and medical images. These parameters are can be used by a therapeutic determining model to recommend therapies, doses, and time courses accurately.

Abstract: An image processing circuit capable of detecting an edge component includes: a selecting circuit acquiring the brightness values of pixels of an image according to the position of a target pixel and a processing region, wherein the pixels include N horizontal lines and M vertical lines; a brightness-variation calculating circuit generating N horizontal-line-brightness-variation values according to brightness variation of the N horizontal lines, and generating M vertical-line-brightness-variation values according to brightness variation of the M vertical lines; a brightness-variation determining circuit choosing a horizontal-line-brightness-variation representative value among the N horizontal-line-brightness-variation values, choosing a vertical-line-brightness-variation representative value among the M vertical-line-brightness-variation values, and choosing a brightness-variation representative value between the two representative values; an energy-variation calculating circuit generating an energy-variation

Abstract: A method for reducing abasing artefacts in an output image may include obtaining a plurality of input images captured by a plurality of cameras, each camera having a different field of view of an environment surrounding a vehicle, wherein the plurality of input images are mapped to the output image to represent the environment, from a predefined virtual point of view. The method may further include for each pixel position in the output image, obtaining a first pixel density value corresponding to a first output pixel position in the output image; and upon determining that the first pixel density value is higher than a threshold, calculating a first output brightness value corresponding to the first output pixel position based at least on a plurality of brightness values corresponding to a plurality of neighboring pixels of a corresponding position in a first input image of the plurality of input images.

Abstract: An apparatus includes a generation unit configured to generate shape information of an object in a captured image, a component acquisition unit configured to acquire an auxiliary light component representing intensity of an auxiliary light at each pixel of the captured image based on a light amount characteristic representing a light amount of the auxiliary light received by the object when the auxiliary light is emitted and the shape information of the object, a first correction unit configured to generate a first corrected image in which color of the captured image is corrected according to environmental light, a second correction unit configured to generate a second corrected image in which color of the captured image is corrected according to the auxiliary light, and a combining unit configured to combine the first corrected image and the second corrected image at a combination ratio calculated based on the auxiliary light component.

Abstract: A detection and tracking system and method using a camera unit on a robot, or alternatively a camera mounted inside the pool overlooking the bottom of the pool, for safety monitoring for use in and around water-related environments. The robot is able to propel itself and move throughout the body of water, both on the surface and underwater, and the camera unit functions both on the surface and underwater. The robot optimizes the cleaning cycle of the body of water utilizing deep learning techniques. The robot has localization sensors and software that allow the robot to be aware of the robot's position in the pool. The camera is able to send its video feed live over the internet, the processing is performed in the cloud, and the robot sends and receives data from the cloud. The processing utilizes deep learning algorithms, including artificial neural networks, that perform video analytics.

Abstract: Techniques for applying one or more machine learning models to a sub-region less than all of an image scene are described. An example is receiving first sub-region from an image; analyzing the received first sub-region of the image using the indicated least one machine learning model to perform the analyzing of the first sub-region of the scene; and outputting a result of the analyzing.

Abstract: An image processing apparatus includes an input unit that inputs an image, and a processor configured to read out a program stored in a memory, and executes the program. The processor is configured to detect an intended subject from the input image by a first detection method, set an intended subject region for the detected intended subject, detect the intended subject from the input image by a second detection method different from the first detection method, and update the set intended subject region by using a detection result of the second detection method.

Abstract: A system for reducing a search area for identifying correspondences identifies an overlap region within a first match frame captured by a match camera. The overlap region includes one or more points of the first match frame that are associated with one or more same portions of an environment as one or more corresponding points of a first reference frame captured by a reference camera. The system obtains a second reference frame captured by the reference camera and a second match frame captured by the match camera. The system identifies a reference camera transformation matrix, and/or a match camera transformation matrix. The system defines a search area within the second match frame based on the overlap region and the reference camera transformation matrix and/or the match camera transformation matrix.

Abstract: Aspects of the disclosure provide methods and apparatuses for point cloud compression and decompression. In some examples, an apparatus for point cloud compression/decompression includes processing circuitry. For example, the processing circuitry in the apparatus for point cloud encoding receives an occupancy map for a point cloud. The occupancy map is indicative of a background portion and a foreground portion for a coding block in an image that is generated based on the point cloud. Then, the processing circuitry devaluates distortions in the background portion of the coding block during an optimization process that results a coding option for the coding block, and encodes the coding block according to the coding option.

Abstract: In an approach for guiding a visually impaired user to position a mobile device appropriately in relation to a screen so that dynamic information on the screen can be reliably extracted and conveyed to the visually impaired user, a processor receives an image captured by a camera of a mobile device. A processor performs object recognition on the image to identify a digital screen and a location of the digital screen in the image. A processor retrieves a template of the digital screen. A processor performs angle-sensitive optical character recognition (OCR) on the location of the digital screen in the image. Responsive to a processor determining text on the digital screen can be extracted, a processor conveys the text to a user. Responsive to a processor determining text on the digital screen cannot be extracted, a processor guides the user to re-orient the mobile device to capture a better image.

Abstract: A driving controller includes a logo detector. The logo detector includes a histogram extractor which receives input image data and extracts a first histogram from logo area data of the input image data, a first histogram regenerator electrically connected to the histogram extractor and configured to receive the first histogram from the histogram extractor to generate a second histogram based on the first histogram and a logo map determiner electrically connected to the histogram extractor and the first histogram regenerator, and configure to select one of the first histogram and the second histogram to generate a first logo map. The driving controller is configured to compensate the logo area data of the input image data using the first logo map.

Abstract: The present disclosure provides a method, device and non-transitory computer storage medium for processing an image. The method includes: obtaining an image by a monocular camera; extracting image features with different levels based on the image; determining a fused feature by fusing the image features with different levels; and determining a depth distribution feature map of the image based on the fused feature, where a pixel value of each pixel point in the depth distribution feature map is a depth value.

Abstract: A vehicular driver monitoring system includes an illumination source that emits non-visible light that illuminates at least a portion of a driver of the vehicle, a reflector disposed at the vehicle and within a line of sight of the illuminated portion of the driver, a camera disposed in the vehicle and having a field of view that encompasses the reflector, and a control having an image processor that processes image data captured by the camera. The reflector reflects at least some non-visible light and allows visible light to pass through. The camera captures image data representative of the non-visible light emitted by the illumination source that reflects off the illuminated portion of the driver of the vehicle and reflects off the reflector so as to be directed toward the camera. The control, responsive to processing of image data captured by the camera, monitors the illuminated portion of the driver.

Abstract: The present invention provides a new image processing device that is robust against a change in capturing conditions. An image processing device 100 has an acquisition unit 110 for acquiring an image, a smoothing unit 120 for smoothing the acquired image with a prescribed smoothing level, a binarization unit 130 for binarizing the smoothed image, and a control unit 140 for making the smoothing unit 120 execute multiple sessions of smoothing differing in the smoothing level.

Abstract: An object identification method and an object identification device, the object identification method comprises: capturing color images and depth images that are aligned; performing motion detection on the captured color images and depth images to acquire a motion start frame and a motion end frame; comparing the motion end frame with the motion start frame in the color images to acquire a set of motion pixels; performing connected component analysis on the acquired set of motion pixels to obtain at least one connected component; and identifying an object in the at least one connected component.