Abstract: The present invention discloses an identification system which includes an image sensor, a storage unit and a comparing unit. The image sensor captures a plurality of images of the motion trajectory generated by a user at different timings. The storage unit has stored motion vector information of a group of users including or not including the user generating the motion trajectory. The comparing unit compares the plurality of images with the motion vector information to identify the user. The present invention also provides an identification method.

Abstract: An image processing system includes a first light projection unit that projects, onto an object, a light pattern for specifying a three-dimensional shape; a second light projection unit that projects, onto the object, substantially uniform light, in which illumination energy is substantially uniform in a cross-sectional direction relative to a light projection direction, at substantially the same angle as in projection performed by the first light projection unit; an image capturing unit that captures images of the object; a generation unit that generates a division image by dividing components of a first captured image, which is captured while light is projected onto the object by the first light projection unit, by components of a second captured image, which is captured while light is projected onto the object by the second light projection unit; and a calculation unit that calculates three-dimensional positions on the object with use of the division image.

Abstract: A method for processing an image of a physical document to enable digital searching of the physical document includes: obtaining a digital copy of the physical document; receiving an instruction to search for a point of interest in the physical document; imaging the physical document and determining that the point of interest is on a surface of the physical document; and projecting, using a projector and onto the surface of the physical document, a visual-aid component that physically overlaps with the point of interest to highlight the point of interest on the surface of the physical document.

Abstract: Systems and methods for optical material characterization of waste materials using machine learning are provided. In one embodiment, a system comprises: an imaging device configured to generate image frames an area and target objects within the area; an object characterization processor coupled to the imaging device and comprising Neural Processing Units and a Neural Network Parameter Set. The Neural Network Parameter Set stores learned parameters utilized by the one or more Neural Processing Units for characterizing the one or more target objects. The Neural Processing Units are configured by the Neural Network Parameter Set to detect a presence of a plurality of different materials within the image frames based on a plurality of different features. For a first image frame of the plurality of image frames, the Neural Processing Units outputs material characterization data that identifies which of the plurality of different materials are detected in the first image frame.

Abstract: A method (100) for recognizing weed in a natural environment may be provided. A digital image of weed in an early development stage is captured (102) among cultivated crop. Areas with a predefined color and texture specification are contoured (104) defining a boundary contour. The weed is displayed (106) together with a frame and a quality indicator. Moreover, the digital image is stored (110) only if a predefined quality criterion is met. Then, unnecessary color information may be reset (112), the digital image is sent (116) for a further examination, and a weed name of the weed of the captured image and a related probability value indicative of a probability of a match between the weed name and the weed of the captured digital image together image is received (118).

Abstract: Systems and methods are disclosed for extracting depth information for an image by identifying a point of interest appearing in at least two images, calculating depth information for the point of interest by evaluating positions of the point of interest within the images with a change in position of the portable device, defining an image region based on a shared characteristic and assigning the depth information calculated for the point of interest to the defined region.

Abstract: A biometric device includes a substrate, an image sensor, an optical layer and at least one infrared light emitting diode (IR LED). The image sensor is disposed on the substrate. The optical layer is disposed on the image sensor and includes a diffraction pattern. The IR LED is disposed on the diffraction pattern of the optical layer. The optical layer is located between the IR LED and the image sensor.

Abstract: Systems and processes can automatically identify lane markings within images through the use of a machine learning model. The machine learning model may use a reduced set of data and output an improved estimate of lane markings by applying normalized data or images to the machine learning model. Each image applied to the model can be normalized by, for example, rotating each of the images such that the depicted roads are horizontal or otherwise share the same angle. By aligning disparate images of roads, it is possible to reduce the amount of data applied to the model or to model generation, and to increase the accuracy of the machine learning model. Further, the use of normalized images by the machine learning model enables a reduction in computing resources used to apply data to the machine learning model to, for example, identify lane markings within images.

Abstract: A prism of an approximately quadrangle-frustum shape is arranged so that a bottom side, out of two parallel surfaces of the prism, is a placing surface side for a finger. A first imaging unit arranged below a top surface parallel to the bottom surface images an image of the finger transmitted through the top surface. A light source radiates light to at least one side surface of a first set of side surfaces, out of two sets of side surfaces of the approximately quadrangle-frustum shape that face each other. A second imaging unit images the image of the finger transmitted through a second set of side surfaces, out of the two sets of side surfaces. An infrared ray light source radiates infrared ray light into the finger so that the infrared ray light is scattered inside the finger and is received by the imaging unit.

Abstract: To make an object image to be displayed on an image processing apparatus that executes bidirectional communication, for example, an optimum display image according to types of information of a display unit, an object, a viewer, and the like. A display area information acquisition unit acquires display area information of the display unit, and an image acquisition unit acquires an input image including the object to be displayed on the display unit. Further, an image information analysis unit executes input image analysis processing, and a display mode determination unit determines a display mode of the object to be displayed on the display unit, applying an analysis result, and displays an output image generated according to the determined display mode on the display unit. Processing for a missing portion of the object in the case of performing full-size display, correction of a line of sight position, and the like are executed.

Abstract: The present invention is an authentication apparatus comprising: a prism of an approximately quadrangle-frustum shape, the prism of the approximately quadrangle-frustum shape is arranged so that a bottom side, out of two parallel surfaces of the prism of approximately quadrangle-frustum shape, is a placing surface side for a finger; a first imaging means is arranged below a top surface parallel to the bottom surface, the first imaging means that images an image of the finger transmitted through the top surface; a light source that radiates light to at least one side surface of a first set of side surfaces, out of two sets of side surfaces of the approximately quadrangle-frustum shape that face each other; and a second imaging means that images the image of the finger transmitted through a second set of side surfaces, out of the two sets of side surfaces.

Abstract: A vision system for a vehicle includes a camera configured to be disposed at a vehicle so as to have a field of view exterior of the vehicle. A processor is operable to process image data captured by the camera. The vision system determines conditions where processing of captured image data degrades in performance due to environmental conditions. The vision system, responsive to a determined condition, determines a safe state for image processing of captured image data for that determined condition. A failsafe algorithm, responsive to processing of image data captured by the camera and responsive to the determined condition, and in accordance with the determined safe state for that determined condition, determines true negatives and avoids false positives and false negatives.

Abstract: A prism includes a large surface at least a portion of which is a placing region for a finger, a small surface parallel to the large surface, and first and second inclined lateral surfaces. A light source emits light to the first inclined lateral surface. A first imaging sensor arranged below the small surface receives a light transmitted from the light source through the small surface to obtain a first image. A second imaging sensor receives a light transmitted from the light source through the second inclined lateral surface to obtain a second image of which fingerprint pattern contrast is enhanced more than that of the first image. An infrared light source emits infrared ray light to the finger. The first imaging sensor receives the infrared ray light transmitted from the infrared light source through the small surface to obtain a third image for a blood vessel of the finger.

Abstract: A sequence of images depicting an object is captured, e.g., by a camera at a point-of-sale terminal in a retail store. The object is identified, such as by a barcode or watermark that is detected from one or more of the images. Once the object's identity is known, such information is used in training a classifier (e.g., a machine learning system) to recognize the object from others of the captured images, including images that may be degraded by blur, inferior lighting, etc. In another arrangement, such degraded images are processed to identify feature points useful in fingerprint-based identification of the object. Feature points extracted from such degraded imagery aid in fingerprint-based recognition of objects under real life circumstances, as contrasted with feature points extracted from pristine imagery (e.g., digital files containing label artwork for such objects).

Abstract: An apparatus includes: a processor configured for obtaining a first image that corresponds with a first multi-leaf collimator (MLC) configuration, wherein the first image is generated when the MLC is stationary, obtaining a second image that corresponds with a second MLC configuration, wherein the second image is generated when the MLC and/or another component of a radiation machine is being operated to track a motion, and performing an analysis based at least in part on the first image and the second image to obtain a result; and a non-transitory medium for storing the result.

Abstract: A method and an apparatus for recognizing an object are disclosed. The apparatus may extract a plurality of features from an input image using a single recognition model and recognize an object in the input image based on the extracted features. The single recognition model may include at least one compression layer configured to compress input information and at least one decompression layer configured to decompress the compressed information to determine the features.

Abstract: Techniques for neural network training are provided. One computer-implemented method comprises: obtaining, by an electronic device operatively coupled to a processing unit, based on a similarity between two images, a first image and a second image. The computer-implemented method also comprises training, by the electronic device, a neural network based on the first image and the second image such that a distance between a first vector and a second vector generated respectively from the first image and the second image in the trained neural network is associated with the similarity.

Abstract: The present invention discloses an identification system which includes an image sensor, a storage unit and a comparing unit. The image sensor captures a plurality of images of the motion trajectory generated by a user at different timings. The storage unit has stored motion vector information of a group of users including or not including the user generating the motion trajectory. The comparing unit compares the plurality of images with the motion vector information to identify the user. The present invention also provides an identification method.

Abstract: A terminal having a fingerprint identification function is provided. The terminal includes: a body having an outside surface; a screen disposed on the outside surface; a fingerprint detection component disposed on the outside surface; and a processor disposed inside the body and electrically connected to the screen and the fingerprint identification component; the processor is configured to turn on the fingerprint detection component to obtain fingerprint data detected by the fingerprint detection component when a touch signal on the screen is received and to execute the preset control instruction if the fingerprint data matches pre-stored reference fingerprint data.

Abstract: The present disclosure relates to a security check system and method. The present disclosure provides a security check system for identifying objects of interest from multiple objects, comprising: an object-of-interest determining device for determining whether an object is an object of interest; an image mark applying device for acquiring images related to selected objects among the multiple objects and recording image marks of the selected objects; and a mark detecting device for detecting the image marks, wherein the security check system is configured to identify whether the object is the object of interest based on the detection of the mark detecting device and outputs a warning accordingly.