Abstract: An image authentication apparatus includes a registration unit, a parameter computing unit, a similarity degree calculation unit, a status acquisition unit, and a generation unit. The registration unit is configured to register an image of an object to be authenticated in a registration dictionary as a registered image. The parameter computing unit is configured to compute a parameter based on the registered image. The parameter is computed for a degree of similarity between an image of the object and the registered image. The similarity degree calculation unit is configured to calculate a degree of similarity between an image of the object and the registered image, using the parameter. The status acquisition unit is configured to acquire a registration status of the registered image. The generation unit is configured to generate a display screen including the registration status, and to output the generated display screen.

Abstract: A living body detection device (1) includes: an image acquisition unit (171), a determination unit (173) and a detection unit (174). The image acquisition unit (171) acquires a first image in which a subject irradiated by light in a first wavelength range is imaged, and a second image in which the subject irradiated by light in a second wavelength range is imaged, the second wavelength range being different from the first wavelength range. The determination unit (173) determines whether a relation expressed by luminance of the subject imaged in the first image and luminance of the subject imaged in the second image is a relation exhibited by a living body. The detection unit (174) detects that the subject is a living body in a case where the determination unit (173) has determined that it is the relation exhibited by the living body.

Abstract: Systems and methods are disclosed for processing an electronic image corresponding to a specimen. One method for processing the electronic image includes: receiving a target electronic image of a slide corresponding to a target specimen, the target specimen including a tissue sample from a patient, applying a machine learning system to the target electronic image to determine deficiencies associated with the target specimen, the machine learning system having been generated by processing a plurality of training images to predict stain deficiencies and/or predict a needed recut, the training images including images of human tissue and/or images that are algorithmically generated; and based on the deficiencies associated with the target specimen, determining to automatically order an additional slide to be prepared.

Abstract: Digital image data including discrete photographic images of a variety of different subjects, times, and so forth, are collected and analyzed to identify specific features in the photographs. In an embodiment of the invention, distinctive markers are distributed to aid in the identification of particular subject matter. Facial recognition may also be employed. The digital image data is maintained in a database and quarried in response to search requests. The search requests include criteria specifying any feature category or other identifying information, such as date, time, and location that each photograph was taken, associated with each photograph. Candidate images are provided for review by requesters, who may select desired images for purchase or downloading.

Abstract: An embodiment of the present disclosure provides a method, an apparatus and a server for determining a mental state of a human, which are used for an augmented reality. The method includes: obtaining a to-be-detected picture; extracting face feature information of a target object from the to-be-detected picture; and inputting the face feature information of the target object into a mental state detecting model to obtain a mental state of the target object. The method, the apparatus and the server for determining a mental state of a human provided by the embodiment of the present disclosure improve the accuracy of the obtained mental state while improving the mental state obtaining efficiency.

Abstract: The current document is directed to methods and systems that employ image-recognition and machine learning to directly measure application-program response time from changes in a user interface displayed by the application program in much the same way that application-program users perceive response times when manually issuing commands through the user interface. The currently disclosed methods and systems involve building recognition models, training the recognition models to recognize application-program states from changes in the user interface displayed by the application program, and using the recognition models to monitor the user interface displayed by an application program to detect and assign timestamps to application-program state changes, from which the elapsed time for various different operations is computed.

Abstract: An electronic device includes a measurement unit configured to measure a contour of a body by the electronic device being moved along a surface of the body and a controller configured to generate a three-dimensional image of the body based on the contour. The controller is configured to generate the three-dimensional image by lining up a plurality of first contours measured along a first direction.

Abstract: In a method for training an image generation model, a first generator generates a first sample matrix, a first converter generates a sample contour image, a first discriminator optimizes the first generator and the first converter, a second generator generates a second sample matrix according to the first sample matrix, a second converter generates a first sample grayscale image, a second discriminator optimizes the second generator and the second converter, a third generator generates a third sample matrix according to the second sample matrix, a third converter generates a second sample grayscale image, a third discriminator optimizes the third generator and the third converter, a fourth generator generates a fourth sample matrix according to the third sample matrix, a fourth converter generates a sample color image, and a fourth discriminator optimizes the fourth generator and the fourth converter. The image generation model can be trained easily.

Abstract: An annotation device, comprising: a display that performs sequential playback display of a plurality of images that may contain physical objects that are the subject of annotation, and a processor that acquires specific portions that have been designated within the images displayed on the display as annotation information, sets operation time or data amount for designating the specific portions, and at a point in time where designation of the specific portions has been completed for the operation time, a time based on data amount, or data amount, that have been set, requests learning to an inference engine that creates an inference model by learning, using annotation information that has been acquired up to the time of completion as training data representing a relationship between the physical object and the specific portions.

Abstract: An apparatus and related methods for enhancing low dynamic range and high dynamic range digital images. The process converts single digital images into a form that can be shown on traditional electronic and computer displays and paper prints through luminance mapping and tone mapping functions. These functions require the calculation of values for each pixel within the digital image. The values calculated include, but are not limited to, color, grey-level, and luminance. The present apparatus and method builds upon the tone mapping process by combining log-average luminance values of various sized neighborhood tiles with the global log-average luminance of the entire image.

Abstract: A device includes at least one processor and memory including instructions that when executed by the at least one processor, cause the at least one processor to scan an input image including pixels that have either a first state or a second state opposite the first state, initiate a first cluster and a first polygon that belongs to the first cluster upon encountering a first pixel of the input image that has the first state, execute a first set of operations to form the first polygon, generate an indication of one or more characteristics of the input image based on at least the first cluster, and output the indication.

Abstract: Systems, apparatuses, and methods are directed towards identifying that an adversarial patch image includes a plurality of pixels. The systems, apparatuses, and methods include dividing the adversarial patch image into a plurality of blocks, that each include a different group of the pixels in which the pixels are contiguous to each other, and assigning a first plurality of colors to the plurality of blocks to assign only one of the first plurality of colors to each pixel of one of the plurality of blocks.

Abstract: The embodiment of the present invention provides a semi-supervised automatic marking method for spartina alterniflora in a hyperspectral image. According to the semi-supervised automatic marking method for spartina alterniflora in a hyperspectral image provided by the present invention, based on the dimensionality reduction on 108-dimensional data of 18 wave bands, unsupervised clustering is performed by the fast clustering algorithm based on the local density, and then the clustering result is matched with a marked spartina alterniflora data set, so that completely automatic marking of the data is realized, and automatic marking for spartina alterniflora is realized. The embodiment of the present invention also provides a semi-supervised automatic marking device for spartina alterniflora in a hyperspectral image. Through the technical scheme provided by the embodiment of the present invention, recognition and marking for spartina alterniflora can be realized accurately and effectively.

Abstract: A three-frame difference target-tracking system includes at least one processor configured to generate multiple aligned image frames of a scene. The aligned image frames include first, second, and third image frames. The at least one processor is also configured to identify differences between the first image frame and the second image frame, between the second image frame and the third image frame, and between the first image frame and the third image frame. The at least one processor is further configured to identify a direction of movement of a target in the scene based on the identified differences.

Abstract: Various embodiments of systems and methods for decentralized image management are described herein. The method includes generating, distributing, and retrieving images on peer-to-peer network. Request for generating an image is received. Multiple components/layers of a to-be-generated image is identified. A layer is stored as a file. Files corresponding to the layers are packaged as an image file representing the image. The packaged image file and/or files of respective layers are distributed across the network, e.g., across a plurality of available nodes upon receiving a distribution command/request. When a request for retrieving the image is received, the nodes storing the multiple layers of the image are identified. The layers are retrieved from the identified multiple nodes. Using the retrieved multiple layers, the image is recreated/generated.

Abstract: The present disclosure relates to a repairing method for Mura in a display panel, including: configuring a rectangular-shaped first black area in a first image displayed in a display region of a display panel to be a width of a first predetermined pixel, determining a boundary “a” of the white area, configuring a second white area in a second image displayed in the display region of the display panel to be a width of a second predetermined pixel, determining a boundary “b” of the black area, obtaining a boundary “c” of an actual-displaying image of the display panel according to a width of a third predetermined pixel within an image captured by a charge couple device (CCD), cutting the image captured by the CCD along the boundary “c”, and conducting a Mura repairing process on the image which has been cut down.

Abstract: Provided is a robot, including: a plurality of sensors; a processor; a tangible, non-transitory, machine readable medium storing instructions that when executed by the processor effectuates operations including: capturing, with an image sensor, images of a workspace as the robot moves within the workspace; identifying, with the processor, at least one characteristic of at least one object captured in the images of the workspace; determining, with the processor, an object type of the at least one object based on characteristics of different types of objects stored in an object dictionary; and instructing, with the processor, the robot to execute at least one action based on the object type of the at least one object.

Abstract: Provided is technique of object recognition that can accurately recognize an object. An object recognition apparatus (i) generates property data that highlights a specific property based on target data, (ii) extracts a discrimination-use feature amount used for discrimination of each piece of the property data, (iii) calculates discrimination information used for discrimination of the property data, (iv) extracts a reliability feature amount used for estimation of reliability of the discrimination information calculated for each piece of the property data, (v) estimates the reliability of the discrimination information, (vi) generates synthesized information acquired by synthesizing the discrimination information calculated for each piece of the property data and the reliability calculated for each piece of the property data, and (vii) performs processing related to the object recognition.

Abstract: A system and method of generating a composite frame from a video capturing a plurality of persons. The method comprises determining a plurality of frames corresponding to occurrence of a predetermined event in the video; determining an importance score for each of the plurality of persons in the determined plurality of frames, the importance score determined based on a type of interaction detected between each of the plurality of persons with an activity object; and selecting one or more of the plurality of persons based on the determined importance score to generate a composite frame of the event including the selected one or more persons.

Abstract: A computer is configured to obtain a digital image (e.g., a video) of a customer in a retail store setting, and analyze the digital image to determine whether the customer was assisted with a particular sales transaction by one or more sales associates. If so, the computer identifies which particular sales associates assisted the customer based on the analysis, and links those sales associates to the customer's sales transaction. Such linking provides a basis for training tools, as well as for the accurate apportionment of a sales commission.