Provided is an expansion electronic device suitable for being disposed at an edge of a main framework having therein a motherboard. The expansion electronic device includes an expansion frame bar and functional module. The expansion frame bar has thereon an expansion box. The expansion box has an access opening. The inner rim of the access opening has an inner annular wall. The access opening is covered with a protective cover. The outer rim of the protective cover has an outer annular wall corresponding in shape to the inner annular wall. A resilient annular surface is defined on the outer surface of the outer annular wall. The resilient annular surface abuts against the inner annular wall to hermetically seal the access opening. The functional module is disposed in the expansion box and electrically connected to a control wire exiting the functional module and electrically connected to the motherboard.

In order to authenticate a user of an electronic device, an image of the user's fingerprint is captured. Before feature information is extracted, the fingerprint image is enhanced via localized normalization thereby increasing contrast within the fingerprint image. Thereafter, feature information, such as key point data, is extracted from the image and compared to a predefined template to determine whether the feature information matches the template. If so, the user is authenticated. By enhancing the quality of the fingerprint image through localized normalization, the reliability of the matching operation is significantly enhanced. In addition, using key point comparisons for assessing similarity between the feature information and the template helps to address inconsistencies relating to finger rotation, scale, and translation during capture.

Electronic fingerprint readers are often used for security such as log-in authentication for the identification of a user for selective access to a computing system. As computing devices shrink in overall size and with downward pressure on device pricing, smaller and less expensive fingerprint readers are increasingly desired. While whole fingerprint readers have the greatest accuracy in user identification, the whole fingerprint is often not required for user identification. Often, only a portion of the user's fingerprint is required to adequately identify the user and thus a small segment fingerprint reader may be sufficient for user authentication. However, the smaller the sensing area of the small-segment fingerprint reader, the more likely that the fingerprint reader misidentifies the user or fails to collect sufficient information to identify the user. Systems and methods for improving identification accuracy of small-segment fingerprint readers are disclosed in detail herein.

A device and method for non-contact optical imaging of a selected surface area of a user's hand, wherein the surface area is actively guided in a non-contact manner into a target position with respect to an image capture unit. For this purpose, the device has a frame in which the hand is inserted, assuming an actual position, roughly related to the target position. In addition, the device contains at least one active means for localizing the respective actual position and an output unit via which feedback is given to the user and the user iteratively guides the surface area into the target position. Advantageously, the device and method are suitable for distinguishing a natural hand from an artificial hand.

The present disclosure provides a fingerprint scanning method and a mobile terminal. The mobile terminal includes a first fingerprint scanning module and a second fingerprint scanning module. The method includes: monitoring an operation performed on a scanning area of the first fingerprint scanning module; when an operation instructing to enter a preset fingerprint application scenario is monitored, transmitting a wake-up instruction to the second fingerprint scanning module. The wake-up instruction is configured to instruct the second fingerprint scanning module to enter an operation mode.

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 light radiated from the display pixel layer and reflected by the object. The electronic device further includes a processor adapted to display, on the display, the fingerprint recognition area when a function associated with a fingerprint recognition is executed.

A method for identifying a user using an image of an object of the user that has a biometric characteristic of the user, like a fingerprint or a set of fingerprints of fingertips, the method comprising: obtaining, by an optical sensor of a mobile device, the image of the object; providing the image or a part of the image to a neural network; processing the image or the part of the image by the neural network, comprising distinguishing, by the neural network, a portion of the image or the part of the image comprising the region of interest, ROI, from another portion of the image; extracting from the image or the part of the image, the ROI; storing the portion comprising the ROI in a storage device and/or providing the portion comprising the ROI as input to an identification means, comprising extracting the biometric characteristic of the ROI and processing the extracted biometric characteristic in order to determine whether the extracted biometric characteristic identifies the user.

A sensor including: a transmitter configured to transmit electromagnetic waves between 1 GHz and 300 GHz; a receiver configured to receive the electromagnetic waves from the transmitter, wherein the transmitter and receiver are positioned in relation to a subject to be scanned such that the receiver receives reflected electromagnetic waves; and a control station for processing the received reflected electromagnetic waves and determining movement of an individual. A method for determining movement of an individual including: transmitting electromagnetic waves between 1 GHz and 300 GHz to a subject to be scanned; receiving reflected electromagnetic waves from the subject; analyzing the electromagnetic waves and reflected electromagnetic waves to determine movement of the individual.

A device and a method for contactless fingerprint acquisition is provided. The contactless fingerprint acquisition device includes a housing including a finger scanning area for at least one finger; at least two image capturing devices located in the housing and arranged in a predetermined baseline distance, each image capturing device having an optical axis in a predetermined angle with the vertical direction; and, a lighting unit in the housing for illuminating the at least one finger. The at least two image capturing devices are operable to acquire a plurality of partial fingerprint images of the at least one finger, and the plurality of partial fingerprint images correspond to different portions of the at least one finger.

A fingerprinting solution that uses neural network (NN) based trained Machine Learning (ML) modules in combination with traditional image processing for contactless fingerprint capture, liveness detection to rule out fake fingers, and fingerprint matching using a portable handheld device with integrated camera, thereby eliminating the need for a special device dedicated for fingerprinting. The trained NN modules detect the size and direction of fingers in the captured image, check if fingers are reversed in the image (thereby making nails visible), check if the thumb of the correct hand is captured, and generate fixed-length fingerprint templates for subsequent matching of fingerprints. Three dimensional (3D) depth map of a finger is used to bring the fingerprint resolution to 500 dpi and eliminate distortion caused by the curvature of the finger shape to improve accuracy while scaling and flattening a fingerprint image. The solution facilitates contactless-to-contactless as well as contactless-to-contact based fingerprint matching.