The present application discloses a display panel having a plurality of pixels, each of which includes at least one subpixel region and an inter-subpixel region, the display panel includes a light filtering layer forming a light filtering region within the inter-subpixel region, the light filtering layer comprising a light filtering material at least partially transmissive for a light of a selected wavelength; and a photosensor in the light filtering region for detecting the light of the selected wavelength, the photosensor being sensitive to the light of the selected wavelength.

The invention relates to a method for biometric processing of images of part of the human body comprising at least one finger, said method being performed by a sensor, and wherein an emissive screen (1) displays at least one first display pattern to light said part of the human body and an imager (2) acquires at least one first image of said part of the human body; from this first image, the automated data-processing system determines at least one second display pattern different to the first display pattern; the emissive screen (1) displays at least the second pattern to light said part of the human body and the imager (2) acquires at least one second image of said part of the human body; a biometric processing being performed on a final image constructed from at least the second image.

A biometric authentication device includes a memory and a processor coupled to the memory, the processor being configured to execute a process, the process including: storing enrollment biometric information; determining the category of biometric information input in a biometric sensor; comparing input biometric information with each enrollment biometric information that is associated with a category determined in the determining with respect to the input biometric information; and associating, when a first comparison between the input biometric information and the each enrollment biometric information is failed and a second comparison between each enrollment biometric information that is associated with a category determined in the determining with respect to re-input biometric information and the re-input biometric information is succeeded, the each enrollment biometric information having achieved a success of the second comparison with the category determined with respect to the input biometric information.

To extract a fingerprint core for alignment of a fingerprint image for fingerprint matching. The present invention comprises: a core extraction unit which has an endpoint processing function of generating an endpoint image by extracting bifurcations in skeleton image and subjecting the respective bifurcations to endpoint processing; and a skeleton image generation/extraction unit which extracts skeletons of a density-inverted image formed by inverting the density colors of the generated end point image from white to black and vice versa, and performs processing for generating the skeleton image, the core extraction unit being provided with a core determination function of specifying a skeleton pixel having the highest value of a loop score indicating the degree of a bend in a skeleton shape in the density-inverted image, and defining this skeleton pixel as the finger print core.

An in-cell optical fingerprint display device has a substrate, a plurality of pixel units disposed on the substrate and arranged in a matrix, and a transparent cover disposed on the plurality of pixel units. At least one pixel unit includes: a display pixel unit at least has a red sub-pixel unit, a green sub-pixel unit, and a blue sub-pixel unit disposed on the substrate; and a fingerprint pixel unit having an optical fingerprint sensor disposed on the substrate, and a specific-color color resin arranged above the optical fingerprint sensor, wherein the specific-color color resin is a blue color resin or a green color resin.

A method for detecting a finger at a fingerprint sensor includes detecting a presence of an object at a fingerprint sensor and, in response to detecting the presence of the object, acquiring image data for the object based on signals from the fingerprint sensor. The method further includes, for each subset of one or more subsets of the image data, calculating a magnitude value for a spatial frequency of the subset, and identifying the object as a finger based on comparing the magnitude value to a threshold.

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.

An optical sensor system includes: an input surface providing a sensing region for a biometric object; a plurality of display elements, disposed beneath the input surface, configured to emit light to provide a display; an aperture layer, disposed beneath the plurality of display elements; a collimator layer, disposed beneath the aperture layer; and a plurality of light sensing elements, disposed beneath the collimator layer, wherein the plurality of light sensing elements are configured to detect light from the sensing region that has passed through the aperture layer and the collimator layer.

A minutia features generation apparatus comprises: an input part to input an image formed as a curved stripe pattern by a ridge line(s); a generation part to generate a skeleton image formed by extracting a skeleton(s) from the image; an extraction part to extract a plurality of minutiae from the skeleton image; and a calculation part configured to calculate a relation minutia feature(s) representing relationship between a first minutia and a second minutia among the plurality of minutiae, wherein the calculation part calculates as one of the relation minutia features defined by a crossing count of the skeleton(s) and a straight line connecting from the second minutia to a nearest neighbor point which is a point on a trace line traced by tracing starting from the first minutia, which point is located at a shortest line distance from the second minutia.