Abstract: A method is disclosed including: receiving raw image data corresponding to a series of raw images; processing the raw image data with an encoder to generate encoded data, where the encoder is characterized by an input/output transformation that substantially mimics the input/output transformation of one or more retinal cells of a vertebrate retina; and applying a first machine vision algorithm to data generated based at least in part on the encoded data.

Abstract: A resolving method and a system, the method includes: creating a sample library by utilization of an original high-resolution (HR) image set; training a convolutional structural network by utilization of the sample library; and obtaining an HR output signal by processing a low-resolution (LR) input signal by utilization of the trained convolutional structural network. In the resolving method and system according to this disclosure, data after expansion may be processed by simple expansion hardware, without a large change algorithm; and complex algorithms are allocated into parallelizing design, and different servers operate mutually independent; and also, due to the modular design, the design proposals of functional modules may be modified by latter optimization.

Abstract: The method of the invention comprises: obtaining a sequence of at least two images, with different levels of illumination; extracting the region containing the sign in the image; calculating the luminance values of the signs; and obtaining the difference in luminance of the sign corresponding to the two levels of illumination. The value obtained is the luminance of the sign (11) corresponding to an illumination equal to the difference between the illuminations, or additional illumination. This result is based on the additive property of luminance, according to which the luminance of a sign is the sum of the luminance produced by each source of illumination. A basic illumination device (5), an additional illumination device (7), at least one camera for taking images, and image recording, positioning and synchronism systems are required to implement the method.

Abstract: An image processing apparatus includes an information obtaining unit configured to obtain three-dimensional polarization sensitive tomographic information and three-dimensional motion contrast information about a subject based on tomographic signals of lights having different polarizations, the lights being obtained by splitting a combined light obtained by combining a returned light from the subject illuminated with a measurement light with a reference light corresponding to the measurement light, an obtaining unit configured to obtain a lesion region of the subject using the three-dimensional polarization sensitive tomographic information, and an image generation unit configured to generate an image in which the lesion region is superimposed on a motion contrast image generated using the three-dimensional motion contrast information.

Abstract: Each of vehicles acquires its own position, and transmits an image of a nearby outside taken by an own camera and a piece of information of the own position. An information center communicatable wirelessly with the vehicles receives the images and the pieces of information of the vehicles' positions transmitted by the vehicles, and recognizes pieces of first character information appearing in the received images, respectively. Based on the received pieces of information of the vehicles' positions as well as at least either points of interest or areas stored as collection target information, the information center determines at least either points of interest or areas for the recognized pieces of first character information, respectively, and stores association information where the pieces of first character information are associated with the determined at least either points of interest or areas.

Abstract: A fingerprint identification device and manufacturing method thereof, and electronic device are disclosed. The fingerprint identification device includes a base film, a detection circuit, and an adhesive layer. The detection circuit is provided at a first side of the base film; the adhesive layer is provided on the first side of the base film, and is provided between the base film and the detection circuit, so as to adhere the detection circuit onto the base film.

Abstract: A tracking device includes: an imaging unit that inputs an image into an image input unit; a first moving body detection unit that calculates an optical flow and detects a position and a direction of movement of a moving body based on the calculated optical flow; a second moving body detection unit that detects a position and a direction of movement based on a plurality of overhead images generated; a third moving body detection unit that detects a position and a direction of movement by integrating detection results from the first and second moving body detection units; a tracked moving body confirmation unit that determines a moving body to be tracked based on detection results from the first to third moving body detection units; an estimation unit that estimates a future position and direction of movement; and a tracking unit that tracks the tracked moving body and identifies a position.

Abstract: The objective of the present invention is to provide an object detection method such that an object such as a vehicle can be detected from an image captured by an on-board camera even when a lens of the on-board camera is dirty. In order to achieve the objective, in this object detection method for detecting an object included in a captured image, an original image including the object to be detected is prepared from the captured image, a processed image is generated from the prepared original image by applying predetermined processing to the original image, and learning regarding restoration of an image of the object to be detected is performed using the original image and the processed image.

Abstract: Embodiments of the invention include a system and set of processes for organizing image collections. The system detects individuals in each image uploaded into the system using facial recognition or similar methods. The user and viewers of the images may then view dynamic albums based on the interrelationships of individuals in images. Users and viewers may browse all images with an individual or see albums of images with two selected individuals or similar combinations based on the relationships between users.

Abstract: Systems and methods for use in identifying a brain condition of a subject are provided. In some aspects, a provided method includes constructing a classifier to identify a brain condition of a subject comprising steps of receiving image data obtained from a plurality of subjects, wherein the image data is acquired during an acquisition period following administration of at least one radioactive tracer. The method also includes defining a plurality of brain condition classes using the image data associated with one or more time frames during the acquisition period, and processing the image data to generate signatures corresponding to each of the plurality brain condition classes. The method further includes constructing the classifier using the signatures. The classifier can then be applied to determine a degree to which the subject expresses one or more disease states in order to determine a brain condition of the subject.

Abstract: An organic light-emitting display panel and a manufacturing method thereof as well as an electronic device are provided. The organic light-emitting display panel includes: an array substrate; a photosensitive identification array including a plurality of photosensitive identification devices; and a photosensitive detection circuit including a common voltage input layer and a photosensitive detection switch. The photosensitive detection switch includes a drain metal layer, a first electrode of the photosensitive identification device is electrically connected with a drain metal layer of an associated photosensitive detection circuit and a second electrode thereof is electrically connected with the common voltage input layer of the associated photosensitive detection circuit.

Abstract: An extraneous-matter detecting apparatus including a dividing unit that divides a captured image into a plurality of regions. The captured image is output from an image capturing device; a computing unit detecting luminance values of pixels included in each of the regions divided by the dividing unit, and computes, for each of target regions, an average value or a standard deviation of luminance values of the detected luminance values. The corresponding target region corresponds to the one or more regions; and a detection unit that extracts the target regions having the average values or the standard deviations of the luminance values computed by the computing unit, which are within a predetermined range, and detects, when the extracted target regions are adjacent to each other, the adjacent target regions as an extraneous-matter region. The extraneous-matter region is a region of the image capturing device to which an extraneous matter is adhered.

Abstract: Embodiments of the disclosure may be directed to an image processing system configured to receive a medical image of a region of a subject's body taken at a first time and to receive a surface image of an exterior portion of the region of the subject's body taken at the first time. The image processing may also be configured to receive a medical image of the region of the subject's body taken at a second time and to register the medical image taken at the first time, the surface image taken at the first time, and the medical image taken at the second time.

Abstract: The present disclosure relates to the technical field of medical image processing and, in particular, to a liver boundary identification method and a system. The method includes: obtaining liver tissue information of a liver tissue to be identified; identifying a liver tissue boundary in the liver tissue information according to a feature of the liver tissue corresponding to the liver tissue information and a feature of the liver tissue boundary corresponding to the liver tissue information using an image processing technology or a signal processing technology; and outputting position information of the identified liver tissue boundary. By using the disclosed method, the liver tissue boundary can be identified automatically, the efficiency of identifying the liver boundary can be improved, and automatic positioning of the liver boundary can thus be achieved.

Abstract: Disclosed is a display device including a display panel configured to be situated under a transparent substrate and display an image on a display area toward the transparent substrate, a fingerprint sensor under the display panel to detect a fingerprint contacting the transparent substrate, and a drive integrated circuit (drive IC) configured to drive the display panel.

Abstract: The present disclosure provides for improved image analysis via novel deblurring and segmentation techniques of image data. These techniques advantageously account for and incorporate segmentation of biological analytes into a deblurring process for an image. Thus, the deblurring of the image may advantageously be optimized for enabling identification and quantitative analysis of one or more biological analytes based on underlying biological models for those analytes. The techniques described herein provide for significant improvements in the image deblurring and segmentation process which reduces signal noise and improves the accuracy of the image. In particular, the system and methods described herein advantageously utilize unique optimization and tissue characteristics image models which are informed by the underlying biology being analyzed, (for example by a biological model for the analytes). This provides for targeted deblurring and segmentation which is optimized for the applied image analytics.

Abstract: A method of detecting failure of an object tracking network with a failure detection network includes receiving an activation from an intermediate layer of the object tracking network and classifying the activation as a failure or success. The method also includes determining whether to initiate a recovery mode of the object tracking network or to remain in a tracking mode of the object tracking network, based on the classifying.

Abstract: The present application relates to an image segmentation method and device operating on an electronic device. The image segmentation method comprises the following steps: performing deep learning to obtain an FCN (Fully Convolutional Network) model, and calculating the loss using L(pji)=?(1?pji)r log(pji) in the deep learning process; inputting an image to be segmented to the last updated FCN model to obtain the probability that each pixel in the image to be segmented is in each of the categories, and selecting the category corresponding to the maximum probability as the category determined by the image segmentation for the pixel. By improving the loss function of the FCN model, the accuracy of image classification is improved, and chart information in an electronic document is accurately extracted by means of pixel classification.

Abstract: According to some aspects, an information processing device is provided. The information processing device includes circuitry configured to set at least one region of an image of a biological sample and select a motion compensation parameter calculated based at least on a motion of the at least one region. The circuitry is further configured to control display of a result of performing a process on the at least one region using the selected motion compensation parameter.

Abstract: The present disclosure relates to a method and system for registering multi-modality images. The method may include: acquiring a first image relating to a registration model, wherein the registration model includes a plurality of reference objects; acquiring a second image relating to the registration model; determining a set of reference points based on the plurality of reference objects; determining a set of mapping data corresponding to the set of reference points in the first image and the second image; and determining one or more registration parameters based on the set of mapping data.