Fingerprint identification control methods, touch panels and display devices are provided. The touch panel includes a substrate, a touch film layer arranged on a side of the substrate, an image processing module arranged on a position corresponding to a preset region of the touch film layer, and the image processing module includes a first module and a second module performing fingerprint identification and image capturing in a time share manner.

The present invention integrates a low power and high compression pixel-wise coded exposure (PCE) camera with advanced object detection, tracking, and classification algorithms into a real-time system. A PCE camera can control exposure time of every pixel in the camera and at the same time can compress multiple frames into a compressed frame. Consequently, it can significantly improve the dynamic range as well as reduce data storage and transmission bandwidth usage. Conventional approaches utilize PCE camera for object detection, tracking and classification, require the compressed frames to be reconstructed. These approaches are extremely time consuming and hence makes the PCE cameras unsuitable for real-time applications. The present invention presents an integrated solution that incorporates advanced algorithms into the PCE camera, saving reconstruction time and making it feasible to work in real-time applications.

A system for detecting scan and non-scan events in a self-check out (SCO) process includes a a scanner for scanning objects and generating point of sale (POS) data, a video camera for generating a video of the scanning region, proximity sensors proximal to the video camera for defining an Area of Action (AoA), wherein the video camera starts capturing scanning region, when the objects enter the AoA, and the POS data includes non-zero values, an Artificial neural network (ANN) for receiving an image frame and generating one or more values, each indicating a probability of classification of the image frame into one or more classes respectively, and a processing unit for processing the POS data, and probabilities of one or more classes to detect a correlation between video data and POS data, and detect one of: scan and non-scan event in the image frame based on the correlation.

In order to detect an unmanned aerial vehicle (UAV) in a monitoring area using a rotatable camera, an integrated sensor configures a first detection area in the monitoring area by rotating the camera after fixing the focal length of the camera to an initial value, and configures a second detection area in the monitoring area by rotating the camera after changing at least one of the focal length of the camera and a rotation path representing a distance from the origin of the monitoring area.

A display module includes: a liquid crystal module, a cover plate, and a texture recognition unit. The texture recognition unit includes a first light source and a texture sensing module. The first light source is located at a side of the cover plate proximate to the liquid crystal module, and is configured to emit invisible light. The texture sensing module is located at a side of the liquid crystal module facing away from the cover plate. A light wavelength range of light allowed to pass through the cover plate and the liquid crystal module includes a light wavelength range of the invisible light. The texture sensing module is configured to collect reflected light after the invisible light is irradiated to a target object, so as to identify a texture of the target object.

A mobile terminal in accordance with one embodiment of the present disclosure include: a flicker sensor configured to recognize a surrounding environment of the mobile terminal; a time of flight (ToF) sensor configured to measure a depth of a subject and a camera configured to capture the subject to generate an image of the subject; and a controller configured to control the camera to recognize the surrounding environment by operating the flicker sensor in response to a user input for operating the camera, to determine a light output to time of the ToF sensor in response to the surrounding environment, and to capture the subject while measuring the depth of the subject by operating the ToF sensor in an operation mode corresponding to the light output time. Other embodiments are also available.

The present disclosure relates to a vehicle door lock having an infrared biometrics information collection device. In certain embodiments, vehicle door lock includes, a vehicle door with a door handle for opening vehicle door, an infrared light source, and an infrared biometrics information collection sensor. The infrared light source includes one or more infrared light emitters. The infrared biometrics information collection sensor captures at least one infrared image of biometrics information of the one or more fingers of a target human hand. The fingers are positioned between the infrared light source and the infrared biometrics information collection sensor. The infrared light source irradiates infrared light through the one or more fingers to generate the infrared image of biometrics information of the one or more fingers on infrared biometrics information collection sensor, and infrared biometrics information collection sensor captures the infrared image of biometrics information of the one or more fingers.

An article recognition device includes an image interface, a distance information interface, a support unit, and a processor. The support unit supports an article at a height equal to or greater than a minimum discrimination distance of a distance sensor from a reference plane of the distance sensor and includes a member of which a distance cannot be measured by the distance sensor. The processor acquires a captured image capturing the article supported by the support unit through the image interface, acquires distance information measured by the distance sensor toward the reference plane through the distance information interface, extracts an area having a height equal to or greater than the minimum discrimination distance from the reference plane as an article area of the article from the captured image based on the distance information, and recognizes the article from an image of the article area.

In accordance with an aspect of the present disclosure, there is provided a vehicle position estimation method. The method comprises, obtaining a landmark-based initial position information of a camera by matching a landmark in a high definition map corresponding to a GPS-based initial position information of a vehicle to an image obtained by the camera of the vehicle, and obtaining estimated position information of the vehicle by comparing the image with a landmark in the high definition map corresponding to each of a plurality of candidate position information sampled based on the landmark-based initial position information of the camera.

Techniques for providing real-time vehicle surveillance is disclosed. An in-vehicle surveillance device continuously captures images from the surroundings of a vehicle and the interior of the vehicle and transmits them to a surveillance management system. The images are processed in real-time using machine learning modules to determine primary, secondary, and adverse events. Upon determining the events, alerts are generated and sent to a display unit provided on the in-vehicle surveillance device to improve the safety of the passengers. The techniques further allow vehicle-to-vehicle communication and vehicle to third party device communication upon determining an event.