Locating morphology in a tissue sample is achieved with devices and methods involving storage of a plurality of feature vectors, each associated with a specific named superpixel of a larger image of a tissue sample from a mammalian body. A microscope outputs, in some embodiments, a live image of an additional tissue sample or a digitized version of the output is used. At least one superpixel of the image is converted into a feature vector and a nearest match between the first feature vector and the plurality of stored feature vectors is made. A first name suggestion is then made based on the nearest match comparison to a store feature vector. Further, regions of interest within the image can be brought to a viewer's attention based on their past history of selection, or that of others.

Irregularities on the surfaces of veneer, such as full veneer sheets and/or veneer core material are detected using Near InfraRed (NIR) technology, including Near InfraRed/Short Wave InfraRed (NIR/SWIR) cameras and detectors. A grade is then assigned to the veneer based, at least in part, on the detected irregularities. The graded veneer is then stacked based, at least in part, on the grade assigned to the veneer. The graded veneer stacks are then provided to local robotic panel assembly and pressing systems that include one or more local robotic panel assembly cells for processing the veneer into layered wood product panels.

An object detection system comprises a polarizer configured to polarize an incoming image scene, a motor controller configured to control a spin rate of the polarizer, a lens configured to collect scene data from the polarized image scene, a first integrated circuit configured to measure the collected scene data at two different and orthogonal polarizations, a second integrated circuit configured to determine a degree of polarization (DoP) and an angle of polarization (AoP) for each image frame pair and to generate pre-processed data, and a processor configured to match the pre-processed data to target criteria. The first integrated circuit can be a DROIC imager and the second integrated circuit can be a FPGA. The AoP and DoP can be determined at a pixel level. The second integrated circuit is configured to apply spatial filtering having a DoP greater than 70% or where AoP is unique to immediate surroundings of AoP.

A key identification system is provided. The key identification system comprises an imaging system to capture an image of a master key, and a logic to analyze the captured image. The imaging system may be capture an image of a groove in the master key from an angle between perpendicular and parallel to the blade of said master key. The logic analyzes the captured image to compare characteristics of the groove with groove characteristics of known key blanks to determine the likelihood of a match between the master key and a known key blank. The key identification system may further compensate for displacement or orientation of the master key with respect to the imaging system when analyzing characteristics of the groove.

The technology disclosed relates to identifying an object in a field of view of a camera. In particular, it relates to identifying a display in the field of view of the camera. This is achieved by monitoring a space including acquiring a series of image frames of the space using the camera and detecting one or more light sources in the series of image frames. Further, one or more frequencies of periodic intensity or brightness variations, also referred to as ‘refresh rate’, of light emitted from the light sources is measured. Based on the one or more frequencies of periodic intensity variations of light emitted from the light sources, at least one display that includes the light sources is identified.

The device for visualizing the interior of a patient's mouth, includes a camera for taking an optical imprint of organs arranged in the mouth. The device includes augmented reality glasses having an optical glass through which a user of the glasses can see the inside of the mouth, and a visualization camera taking an image of what the user sees through the optical glass. First images corresponding to those taken by the visualization camera are correlated with second images corresponding to those taken by the camera for taking an optical imprint, whereby the second images can be projected onto the optical glass.

Systems and methods for authenticating handbags using a portable electronic device along with a bilinear convolutional neural network (CNN) model are described. One method includes using a portable electronic device comprising a camera, and a lens-accessory attached to the portable electronic device such that an optical feature of the lens-accessory is positioned in front of the camera. The portable electronic device acquires one or more pictures of a handbag and sends the one or more pictures to a bilinear CNN model via a network asset where an authenticity is determined. The systems and methods disclosed are capable of allowing the portable electronic device to be spaced apart from the handbag while acquiring pictures, and the lens-accessory can be between 10× and 50× magnification.

Systems and methods for monitoring of icon in an external display device are disclosed. Images of an icon displayed in a display device may be continually captured as video frames by a video camera of an icon monitoring system. While operating in a first mode, video frames may be continually analyzed to determine if the captured image matches an active template icon known to match the captured image of the icon. While the captured image matches the active template icon, operating in the first mode continues. Upon detecting a failed match to the active template icon, the system starts operating in a second to search among known template icons for a new match. Upon finding a new match, the active template icon may be updated to the new match, and operation switches back to the first mode. Times of transitions between the first and second modes may be recorded.

A key identification system is provided. The key identification system comprises an imaging system to capture an image of a master key, and a logic to analyze the captured image. The imaging system may be capture an image of a groove in the master key from an angle between perpendicular and parallel to the blade of said master key. The logic analyzes the captured image to compare characteristics of the groove with groove characteristics of known key blanks to determine the likelihood of a match between the master key and a known key blank. The key identification system may further compensate for displacement or orientation of the master key with respect to the imaging system when analyzing characteristics of the groove.

A method of evaluating equivalence of detection performances of an object to be photographed using a film image and a digital image. The method includes acquiring digital images of the object with varying values of an influence parameter; acquiring digital detection limit values of the respective digital images; specifying a digital detection limit value with highest detection performance from the digital detection limit values; determining that there is equivalence when the specified digital detection limit value is equal to or more than a film detection limit value of the film image, because the detection performance of the object using the digital image assures the detection performance of the object using the film image; and determining that there is no equivalence when the specified digital detection limit value is smaller than the film detection limit value.