A fingerprint classification system and method for extracting the dominant singularity from a fingerprint image are described. The fingerprint classification system and method receive as an input a digital fingerprint image and the image is preprocessed to generate an enhanced and more accurate image. Feature pattern calculations are performed on the updated image to generate an Orientation Feature Vector. The Orientation Feature Vector is processed using a Regular Expression Machine classifier prediction model to generate a class label for the digital fingerprint image that was input.

A touchscreen, now incorporated in most smartphones, tablets, laptops, and similar devices, presents an effective and transparent method to incorporate continuous active user verification schemes. The touchscreen element grid structure can be used to capture information, such as a set of one-dimensional time-varying signals produced as the user's finger moves past the grid intersections points. This information may be used to verify the user, or that a valid user currently has possession of the mobile device, even while the user is not consciously engaged in an active verification process. Further functions, such as habitual gesture recognition, can also be performed using the same grid outputs.

A ridge flow based fingerprint image quality determination can be achieved independent of image resolution, can be processed in real-time and includes segmentation, such as fingertip segmentation, therefore providing image quality assessment for individual fingertips within a four finger flat, dual thumb, or whole hand image. A fingerprint quality module receives from one or more scan devices ridge-flow—containing imagery which can then be assessed for one or more of quality, handedness, historical information analysis and the assignment of bounding boxes.

A fingerprint sensor includes a pixel array, an analog-to-digital converter, and a reference signal generator. The pixel array includes a plurality of unit pixels arranged in rows and columns, and each of the plurality of unit pixels generates an analog signal by detecting a fingerprint of a user. The analog-to-digital converter performs an analog-to-digital conversion operation on the analog signal to generate a digital signal. The analog-to-digital converter is configured to perform the analog-to-digital conversion based on a reference signal. The reference signal generator generates the reference signal such that the reference signal decreases at a first rate from a start voltage, and adjusts a magnitude of the start voltage based on the digital signal.

An electronic device includes a plurality of CMOS control elements arranged in a two-dimensional array, where each CMOS control element of the plurality of CMOS control elements includes two semiconductor devices. The plurality of CMOS control elements include a first subset of CMOS control elements, each CMOS control element of the first subset of CMOS control elements including a semiconductor device of a first class and a semiconductor device of a second class, and a second subset of CMOS control elements, each CMOS control element of the second subset of CMOS control elements including a semiconductor device of the first class and a semiconductor device of a third class. The plurality of CMOS control elements are arranged in the two-dimensional array such that CMOS semiconductor devices of the first class are only adjacent to other CMOS semiconductor devices of the first class, CMOS semiconductor devices of the second class are only adjacent to other CMOS semiconductor devices of the second class, and CMOS semiconductor devices of the third class are only adjacent to other CMOS semiconductor devices of the third class.

An electronic device and method are disclosed. The electronic device includes a cover glass, a display panel, a fingerprint sensor, and a processor. The processor implements the method, including: obtaining, through a fingerprint sensor, a fingerprint image from an external object contacting a surface of the electronic device, detecting, using a processor, a feature point of the fingerprint image, comparing the detected feature point of the fingerprint image with a feature point of a pre-stored reference image, detecting a variation in a distance between the surface of the electronic device and the fingerprint sensor based on a result of the comparison, and recognizing the fingerprint based on the detected variation in the distance.

A texture image acquisition method, a texture image acquisition circuit and a display panel are provided. The texture image acquisition circuit includes a photosensitive circuit, the texture image acquisition method includes: allowing the photosensitive circuit to receive light from a texture, and obtaining a first curve based on a signal amount accumulated by the photosensitive circuit within a first integral time period, the first curve being a time-varying curve of a residual signal amount which is a signal amount remaining after a signal amount, left over by the photosensitive circuit before the first integral time period, is released over time; obtaining a first acquisition value based on a signal amount accumulated by the photosensitive circuit within a second integral time period which is after the first integral time period; obtaining a first photosensitive signal of an image of the texture based on the first curve and the first acquisition value.

A texture recognition device and a display device are provided. The texture recognition device includes a backlight element, configured to provide first backlight; a light constraint element, configured to perform a light divergence angle constraint process on the first backlight to obtain second backlight with a divergence angle within a preset angle range, the second backlight being transmitted to a detection object; and a photosensitive element, configured to detect the second backlight reflected by a texture of the detection object to recognize a texture image of the texture of the detection object.

Certain aspects of the present disclosure provide techniques for selectively activating a fingerprint sensor in an electronic device. A method that may be performed by the electronic device includes detecting a finger hover above the display module, activating the fingerprint sensor based, at least in part, on the detected finger hover, and providing, in response to detecting the finger hover, feedback information to assist in scanning the finger using the fingerprint sensor.

A system comprises an eyewear device that includes a frame, a temple connected to a lateral side of the frame, a fingerprint sensor, and a sensing circuit. The fingerprint sensor includes an input surface to receive input of a finger skin surface. The sensing circuit is configured to track a pattern of fingerprint ridges of the finger skin surface on the input surface. Execution of programming by a processor configures the system to perform functions to track, via the sensing circuit, the pattern of fingerprint ridges of the finger skin surface on the input surface; generate a fingerprint image having the tracked pattern of fingerprint ridges; extract fingerprint features from the fingerprint image; and authorize the user to utilize the eyewear device based on the extracted fingerprint features.