An artificial neural network-based method for detecting a surface pattern of an object includes receiving a plurality of object images, dividing each object image into a plurality of image areas, designating at least one region of interest from the plurality of image areas of each of the object images, and performing deep learning with the at least one region of interest to build a predictive model for identifying a surface pattern of the object.

An image scanning method for a metallic surface and an image scanning system thereof are provided. The method includes sequentially moving one of a plurality of areas on a metallic surface of an object to a detection position, providing far infrared light by a light source component facing the detection position, wherein a light wavelength of the far infrared light is associated with the object, the far infrared light illuminating the detection position with a light incident angle of less than or equal to 90 degrees relative to a normal line of the area located at the detection position, and capturing a detection image of each of the areas sequentially located at the detection position by a photosensitive element according to the far infrared light, wherein the photosensitive element faces the detection position and a photosensitive axis of the photosensitive element is parallel to the normal line.

The invention relates to a biometric sensing system, comprising: a light emitter, a polarization sensor, and a signal processing module, wherein the polarization sensor includes a first polarizer and a second polarizer. First, the light emitter emits a plurality of emitted light from the object under sensing, and reflected by the object. Then, a first reflected light in a first polarization direction and a second reflected light in a second polarization direction in the reflected light are sensed by the polarization sensor. Finally, the signal processing module calculates a first reflectance and a second reflectance according to the first reflected light and the second reflected light, and generate a reflectance ratio based on the first reflectance and the second reflectance. As such, the user determines whether the surface of the object under sensing is 3D by the reflectance ratio, so as to achieve improving safety and saving costs.

The present disclosure discloses a display and input apparatus, including a display panel and an image sensor module. The display panel includes a display substrate, a display array, and a cover plate; a display pixel includes at least two types of sub-pixels that emit lights of different colors; a slit is disposed between pixel electrodes of two adjacent sub-pixels; in the display array, a pixel definition layer is disposed along the slit, and a plano-concave lens array is disposed along the pixel definition layer; each of the plano-concave lenses has its optical axis perpendicular to the display panel and passing through the center of the slit; and during image sensing, the display pixel emits light and illuminates an imaging object on the cover plate, and the image sensor module acquires a reflected image from a surface of the imaging object.

The invention relates to a device for the biometric acquisition and processing of an image of a part of the human body with dermatoglyphs, comprising a contact surface (3) configured so that the part of the human body is affixed to this contact surface (3), a light source (4) configured to project onto the part of the human body a light pattern having a sinusoidal modulation of light intensity in a main direction with a target frequency, an imager (2) configured to acquire an image, and an automated data processing system (7) configured to implement a fraud detection method and a biometric identity recognition method using a periodic component parameter representative of an amplitude of a sinusoidal oscillation of light intensity in the acquired image in accordance with the main direction at the target frequency.

A fingerprint identification apparatus and an electronic device are provided. The fingerprint identification apparatus is used to be disposed under a display screen of an electronic device, including: a sensor chip, where the sensor chip includes a light detecting array and a chip seal ring, and the chip seal ring is disposed around the light detecting array; a light shielding layer, formed on the light detecting array, where the light shielding layer is provided with a plurality of light passing apertures, and the light shielding layer covers an whole region of the light detecting array and at least covers partial region of the chip seal ring; and the fingerprint light signal, returned after reflection or scattering via a finger above the display screen, is transmitted to the light detecting array through the plurality of light passing apertures on the light shielding layer for fingerprint identification.

An image processing device used on a mobile body has: a determiner configured to determine one out of a plurality of combination patterns as to the presence or absence of an object in a plurality of predetermined regions around the mobile body; and a generator configured to generate a composite image by projecting onto a virtual projection surface a plurality of shot images acquired by a plurality of cameras taking images of the surroundings of the mobile body. The generator is configured to select, out of a plurality of projection surfaces prepared beforehand, the projection surface used in generating the composite image in accordance with the combination pattern determined by the determiner.

A distance measurement system includes two or more line pattern generators (LPGs), a camera, and a processor. Each LPG emits a line pattern having a first set of dark portions separated by a respective first set of bright portions. A first line pattern has a first angular distance between adjacent bright portions, and a second line pattern has a second angular distance between adjacent bright portions. The camera captures at least one image of the first line pattern and the second line pattern. The camera is a first distance from the first LPG and a second distance from the second LPG. The processor identifies a target object illuminated by the first and second line patterns and determines a distance to the target object based on the appearance of the target object as illuminated by the first and second line patterns.

An image acquisition section of an information processing apparatus acquires, from an imaging apparatus, polarization images in a plurality of orientations. A normal acquisition section of an image analysis section detects a surface of a subject by acquiring a normal vector on the basis of orientation dependence of polarization luminance. A surface assumption section assumes the presence of an undetected surface continuing from the detected surface. A subject detection section confirms whether or not the assumed surface is present using a normal vector estimated for the assumed surface. An output data generation section generates and outputs output data using information regarding the detected surface.

A implicit structured light decoding method, a computer equipment and a computer-readable storage medium. The method includes: traversing an image captured by a camera to acquire a grayscale value of each pixel point and an ideal neighborhood grayscale distribution; extracting and outputting an updated output image according to the grayscale value of each pixel point and the ideal neighborhood grayscale distribution and in combination with a preset output image; classifying stripe central points in the updated output image into different stripes; determining a correspondence between stripes in the updated output image and stripes in a structured light image according to the different stripes; and decoding all stripe central points by using triangulation method in combination with the correspondence between the extracted stripes and the projected stripe pattern. This solution can efficiently and robustly decode the implicit stripe-based structured light on a basis of ensuring precision.