In an aspect, a fingerprint sensing module configured to be integrated in a device for biometric authentication of a user of the device is provided. The fingerprint sensing module comprises a fingerprint sensor and a display configured to display information to the user; the display comprising pixel elements being arranged in the display such that the pixel elements do not obscure a sensing area of the fingerprint sensor in which area the fingerprint sensor is being configured to detect a finger of the user.

A fingerprint unlocking method, includes obtaining a fingerprint image through an optical fingerprint sensor of an electronic device when a user performs fingerprint unlocking on the electronic device; obtaining an extended fingerprint image by performing fingerprint extending processing on the fingerprint image according to a preset curvature; and unlocking the electronic device if the extended fingerprint image matches a preset fingerprint image.

Biometric gallery management is performed by association one or more wireless identifiers that correspond to one or more mobile devices (such as smart phones, tablet computing devices, cellular telephones, wearable devices, smart watches, fitness monitors, digital media players, medical devices, and/or other mobile computing devices) that people carry with digital representations of biometrics corresponding to the people. Wireless identifiers corresponding to mobile devices proximate to a biometric reader device may be monitored. Upon detection of wireless identifiers corresponding to mobile devices proximate to the biometric reader device, the associated digital representations of biometrics may be loaded from a main gallery into one or more local galleries, which may then be used to perform one or more biometric identifications and/or verifications.

An electronic device is provided. The electronic device includes a display panel, an image lens positioned under the display panel to form a fingerprint image by using light reflected from user fingerprints, an image sensor configured to convert an image into an electrical signal, a first aperture positioned on a first surface between the image lens and the image sensor to block a light component scattered on the display panel, a relay lens positioned between the first surface and the image sensor to collect light having passed through the first aperture to the image sensor, and a second aperture positioned on a second surface between the relay lens and the image sensor to block a light component scattered on the display panel.

A method for monitoring a mobile input device with a screen on which information can be displayed in a first pixel raster of image elements and which comprises a flat optical fingerprint reader and a second pixel raster of light-sensitive sensor elements. A fingerprint and fingerprint characteristics, comprising position of the finger on the screen are detected. The sensor elements detect the light intensity incident on them. The intensity levels are assembled into a static pattern of the fingerprint. The combination of the static pattern and the fingerprint characteristics are compared with a database. If the combination is in the database, a check is carried out whether an action is associated with this combination, which is then carried out, or whether no action is associated with this combination, whereupon a first standard action is carried out. If the combination is not stored, a second standard action is carried out.

The present disclosure relates to a method performed in a fingerprint analysis system for facilitating differentiating between a live finger and a spoof finger. The method comprises acquiring a plurality of time-sequences of images, each of the time-sequences showing a respective finger as it engages a detection surface of a fingerprint sensor. Each of the time-sequences comprises at least a first image and a last image showing a fingerprint topography of the finger, wherein the respective fingers of some of the time-sequences are known to be live fingers and the respective fingers of some other of the time-sequences are known to be spoof fingers. The method also comprises training a machine learning algorithm on the plurality of time-sequences to produce a model of the machine learning algorithm for differentiating between a live finger and a spoof finger.

An under-screen fingerprint sensing device and fingerprint sensing method are provided. The under-screen fingerprint sensing device includes a fingerprint sensor and a processor. The processor performs a first FFC on a first color original value, a second color original value, and a third color original value provided by the fingerprint sensor to determine whether a target object is a real finger. When the processor determines that the target object is an unreal finger, the processor performs a second FFC on the first color original value, the second color original value, and the third color original value to determine again whether the target object is the real finger.

A fingerprint recognition-based synchronous application starting method and device. By providing a sensing unit below a fingerprint recognition area of a display unit, when a user needs to start an application, the user only needs to synchronously click an icon corresponding to an application to be started in the fingerprint recognition area of the screen; the sensing unit acquires fingerprint information of the user, and then compares the acquired fingerprint information with preset fingerprint information, to start the application or perform unlocking. Compared with an existing approach for a mobile apparatus to start an application by means of fingerprint recognition, the method and device improves the operability of application icons on a screen and enhances user experience, and can also effectively reduce the overall thickness of a mobile apparatus, making the mobile apparatus thinner and lighter to meet the market demands.

The present invention relates to a method for classifying a biometric trait represented by an input image, the method being characterized in that it comprises the implementation, by data processing means (21) of a client (2), of the steps of: (a) Determining, for each of a predefined set of possible general patterns of biometric traits, by means of a convolutional neural network, CNN, whether said biometric trait presents or not said general pattern.

The invention provides an image scanning device and an image scanning method. The image scanning device includes: a display that emits red light, green light, and blue light to expose an object when the object contacts the display; the sensor is arranged below the display, and the sensor obtains a first image corresponding to the red light, a second image corresponding to the green light and a third image corresponding to the blue light; and the processing module is coupled to the sensor and the display, and the processing module generates an object image corresponding to the object according to the first image, the second image and the third image.