Abstract: A fingerprint verification method includes selecting one or more first fingerprint groups from among a plurality of fingerprint groups based on an input fingerprint image, each fingerprint group of the plurality of fingerprint groups including partial fingerprint images; and determining whether verification is successful based on the input fingerprint image and each of the partial fingerprint images included in the one or more first fingerprint groups.

Abstract: A dermatoglyph detector includes a detection circuit and an electronic processor unit. The detection circuit includes an electrically conductive thin film in which there are formed both electrodes that are arranged to come into contact with the skin of a portion of a human body and also conductive tracks connecting the electrodes to the processor unit. The processor unit is arranged to determine electrical characteristics of the body portion extending between each pair of electrodes in contact with the skin, and to execute a computer program for acting on the basis of the determined electrical characteristics to distinguish between an authentic body portion and a fake body portion. The detection circuit includes at least two track segments of different shapes between two calibration terminals so as to present an impedance ratio that is not equal to unity.

Abstract: Methods and systems of inserting image files into a container are described herein. One method includes overseeing a submission of images to containers, retrieving a job of inserting images into the container, and inserting images into the container by, for each of the plurality of images: (i) reading and analyzing source data including the image; (ii) opening the container, which includes records, where the image will be stored; (iii) determining whether the source data is valid to be entered into a record; (iv) responsive to a determination that the source of data is valid, preparing metadata; (v) writing the record into the container; and (vi) marking a status flag/mark of the record as being updated while writing the record into the container.

Abstract: A computer-implemented method, for verifying an electronic device user, comprising the steps of issuing at least one action instruction to an electronic device user using a notification mechanism of the electronic device; recording response data from a plurality of data acquisition systems of the electronic device, the response data pertaining to the user's response to the at least one action instruction; processing the response data to form classification scores; combining the classification scores to form a classification value; and verifying the user if the classification value satisfies a threshold, wherein each of the at least one action instruction comprises a liveness challenge.

Abstract: The present application discloses a positioning method for a movable platform, including: detecting, by a laser positioning system (LPS) mounted on the movable platform, a plurality of reflectors mounted on a target object, wherein the movable platform is moving; calculating in real-time, by the LPS, according to the current position information, relative positions of the plurality of reflectors with respect to the LPS; and obtaining, by the LPS, a relative position of the movable platform with respect to the target object based on the relative positions of the plurality of reflectors with respect to the LPS. The present application also discloses positioning system that performs the positioning method.

Abstract: This disclosure is directed to techniques in which a first user in an environment scans visual indicia associated with an item, such as a barcode, before handing the item to a second user. One or more computing devices may receive an indication of the scan, retrieve image data of the interaction from a camera within the environment, identify the user that received the item, and update a virtual cart associated with the second user to indicate addition of the item.

Abstract: An auxiliary prediction system is provided to predict reliability of an object after a specific operation is applied to the target object. The auxiliary prediction system includes an image correction module and an analysis module. The image correction module performs an image correction procedure to convert an original image of the target object into a first correction image. The analysis module performs a feature analysis on the first correction image through an artificial intelligence model that has been trained, so as to predict whether the target object has a defect or not after the specific operation.

Abstract: A method for identifying occupant-specific settings for a vehicle comprises detecting a vehicle occupant; collecting biometric occupant data of the detected vehicle occupant; assembling a descriptor based on at least part of the collected occupant data; storing the descriptor in a database; and updating a cluster of descriptors in the database based on the assembled descriptor, wherein descriptors grouped in the cluster are close to each other, and wherein the cluster corresponds to the detected vehicle occupant. Based on the cluster and assembled descriptor can be assigned to the cluster, and vehicle setting data can be calculated that has been stored in association with the cluster. The vehicle setting data corresponds to occupant-specific settings for the vehicle. A vehicle comprises a system capable of performing such method.

Abstract: This disclosure relates to various implementations that dynamically adjust one or more shallow depth of field (SDOF) parameters based on a designated, artificial aperture value. The implementations obtain a designated, artificial aperture value that modifies an initial aperture value for an image frame. The designated, artificial aperture value generates a determined amount of synthetically-produced blur within the image frame. The implementations determine an aperture adjustment factor based on the designated, artificial aperture value in relation to a default so-called “tuning aperture value” (for which the camera's operations may have been optimized). The implementations may then modify, based on the aperture adjustment factor, one or more SDOF parameters for an SDOF operation, which may, e.g., be configured to render a determined amount of synthetic bokeh within the image frame.

Abstract: An electronic device is provided that includes a display in which a fingerprint recognition area is formed and which includes a display pixel layer, and a rear panel, formed under the display, having a first hole. The electronic device also includes a bracket, disposed under the rear panel, having a sensor accommodating area corresponding to a fingerprint sensor. The electronic device additionally includes the fingerprint sensor disposed under the display pixel layer and adapted to acquire image information to be used for authentication of a fingerprint using at least partially light radiated from the display pixel layer and reflected by the object. The sensor accommodating area has a second hole passing through the bracket, and the fingerprint sensor is disposed in the sensor accommodating area such that an air gap between the display and the fingerprint sensor is formed at least by a portion of the second hole.

Abstract: An example embodiment includes: a determination unit that, based on an image including an eye of a recognition subject, determines whether or not a colored contact lens is worn; and a matching unit that, when it is determined by the determination unit that the colored contact lens is worn, performs matching of the iris by using a feature amount extracted from a region excluding a predetermined range including an outer circumference of the iris out of a region of the iris included in the image.

Abstract: A camera system comprises an image capturing device, object detection module, object tracking module, and match classifier. The object detection module receives image data and detects objects appearing in one or more of the images. The object tracking module temporally associates instances of detected objects, each of which has a signature representing features of the detected object. The match classifier matches object instances by analyzing data derived from the signatures. The match classifier determines whether the signatures match.

Abstract: Techniques are described for optimizing deep learning model performance using image harmonization as a pre-processing step. According to an embodiment, a method comprises decomposing, by a system operatively coupled to a processor, an input image into sub-images. The method further comprises harmonizing the sub-images with corresponding reference sub-images of at least one reference image based on two or more different statistical values respectively calculated for the sub-images and the corresponding reference-sub images, resulting in transformation of the sub-images into modified sub-images images. In some implementations, the modified sub-images can be combined into a harmonized image having a more similar appearance to the at least one reference image relative to the input image.

Abstract: A computer system can implement a network service by receiving, from a computing device of a user, image data comprising an image of a record. The computer system can then execute image processing logic to determine a set of information items from the image. The computer system may then execute augmentation logic to process the record by (i) accessing a transaction database to identify a plurality of transactions made by the user, (ii) identifying a matching transaction from the plurality of transactions that pertains to the record, and (iii) resolving the set of information items using the matching transaction.

Abstract: The image processing device includes an imaging unit that images a subject and a distance map acquisition unit that acquires information regarding a distance distribution of the subject as map data. The distance map acquisition unit acquires map data with an image deviation amount or a defocused amount related to a captured image or distance map data in conformity with a TOF scheme or an imaging plane phase difference detection scheme of using a pupil division type image sensor. An image processing unit generates data of a texture image in which a low-frequency component of a captured image is inhibited and combines the data of the texture image and the map data acquired by the distance map acquisition unit to generate image data in which a distance distribution of a subject is expressed.

Abstract: A computer-implemented method for extracting information from a document, for example an official document, is disclosed. The method comprises acquiring an input image comprising a document portion; performing image segmentation on the input image to form a binary input image that distinguishes the document portion from the remaining portion of the input image; estimating a first image transform to align the binary input image to a binary template image, using the first image transform on the input image to form an intermediate image; estimating a second image transform to align the intermediate image to a template image; using the second image transform on the intermediate image to form an output image; and extracting a field from the output image using a predetermined field of the template image.

Abstract: A system for detection and identification of objects and obstacles near, between or on railway comprise several forward-looking imagers adapted to cover each different range forward and preferably to be sensitive each to different wavelength of radiation, including visible light, LWIR, and SWIR. The substantially homogeneous temperature along the rail the image of which is included in an imager frame assists in identifying and distinguishing the rail from the background. Image processing is applied to define living creature in the image frame and to distinguish from a man-made object based on temperature of the body. Electro optic sensors (e.g. thermal infrared imaging sensor and visible band imaging sensor) are used to survey and monitor railway scenes in real time.

Abstract: According to one embodiment, a model update support system supports an update of a first model trained using a training data group. The training data group includes a plurality of labeled data and includes a plurality of labels respectively labeling the plurality of labeled data. The system includes a processor. The processor is configured to output first information or second information based on a classification certainty and a plurality of similarities. The classification certainty is calculated using the first model and indicates a sureness of a classification of first data. The plurality of similarities respectively indicates likenesses between the first data and the plurality of labeled data. The first information indicates that the training of the first model is insufficient. The second information indicates that one of the plurality of labels is inappropriate.

Abstract: Systems and techniques are described herein for performing optical flow estimation for one or more frames. For example, a process can include determining an optical flow prediction associated with a plurality of frames. The process can include determining a position of at least one feature associated with a first frame and determining, based on the position of the at least one feature in the first frame and the optical flow prediction, a position estimate of a search area for searching for the at least one feature in a second frame. The process can include determining, from within the search area, a position of the at least one feature in the second frame.

Abstract: Provided is a method for developing a geographic agnostic machine learning model. The method may include selecting transaction data associated with payment transactions conducted by a first plurality of users, wherein the transaction data includes first transaction data associated with payment transactions conducted by a first plurality of users in a first geographic area and second transaction data associated with payment transactions conducted by a second plurality of users in a second geographic area, formatting the first transaction data associated with payment transactions conducted by the first plurality of users in the first geographic area and the second transaction data associated with payment transactions conducted by the second plurality of users in the second geographic area to provide training data, and generating the geographic agnostic machine learning model using the training data. A system and computer program product are also disclosed.