236 results about "Fingerprint image" patented technology

The invention relates to the technical field of fingerprint identification, and discloses a small-area fingerprint identification method and device, and a medium. The method comprises the following steps: acquiring a to-be-identified fingerprint image; performing ridge line feature point extraction on the to-be-identified fingerprint image to obtain a feature point set; the feature point set comprises a first feature point and / or a second feature point, the first feature point is a bifurcation point and / or an end point of a fingerprint ridge line, and the second feature point is a maximum curvature point of the fingerprint ridge line; based on feature points in the feature point set, performing image feature extraction on the to-be-identified fingerprint image to obtain a plurality of corresponding local fingerprint image features; and performing feature matching on the local fingerprint image features and preset target fingerprint image features, and generating a fingerprint identification result of the to-be-identified fingerprint image based on a feature matching result. According to the embodiment of the invention, the recognition precision of small-area fingerprint recognition can be improved.

The invention provides an engineering machinery man-machine binding card punching management system based on fingerprint biological recognition, and belongs to the field of fingerprint recognition, and the method comprises the steps: obtaining a fingerprint image of a to-be-recognized constructor and an initial fingerprint matching degree; dividing the fingerprint image of the construction personnel to be identified into a plurality of areas; obtaining a normal fingerprint area and a suspected stain area according to the shape of each area; according to the number of normal fingerprint areas around each suspected dirty area and the distribution of pixel points in each suspected dirty area, obtaining a dirty area; and completing identification according to the normal fingerprint area, the stain area and the initial fingerprint matching degree of the to-be-identified constructor. The invention aims to solve the problem that the construction personnel cannot identify the fingerprint when performing fingerprint card punching identification on the construction site due to the fact that the fingers of the constructor may be stained with oil stains, soil and the like in the construction process. And the problem that fingerprint card punching comparison is wrong may occur.

A fingerprint information processing apparatus includes: an output unit that outputs a certainty factor that is an index indicating probability in which fingerprints indicated by a fingerprint image correspond to at least one of a plurality of pattern types, by using the fingerprint image and a learning model constructed by machine learning using learning data including a sample image indicating fingerprints; and a processing unit that performs processing based on the certainty factor.

Disclosed is a method for providing a trained machine learning system for classifying images of fingerprints, the method comprising: providing a training data set, comprising sets of images of fingerprints, wherein each image in the training data set further comprises a binary label encoding a class designation; using the training data set to train a machine learning system, wherein the machine learning system comprises a classical machine learning model implemented on a classical processor and a quantum machine learning model implemented on a quantum processing unit (QPU); encoding the image data of each image in the training data set into a feature vector using the classical machine learning model, obtaining a family of feature vectors; using the family of feature vectors obtained from the images in the training data set to train the classical machine learning model and the quantum machine learning model, for providing the trained machine learning system, comprising a trained classical machine learning model and a trained quantum machine learning model.

The invention discloses a fingerprint verification method and device based on double-finger fingerprint image acquisition, and relates to the technical field of biological recognition, and the method comprises the following steps: deploying a light sensor, carrying out the primary adjustment of an illumination light source, collecting the light intensity data of the fingerprint surface when two fingers press through the light sensor, and obtaining a fingerprint verification result according to the light intensity data; the method comprises the following steps: deploying a light sensor, constructing a closed-loop adjustment mechanism of primary adjustment, secondary adjustment and quality feedback, acquiring light intensity data of the fingerprint surfaces of the two fingers in real time, judging an abnormal condition, performing secondary adjustment on an illumination light source, acquiring fingerprint images of the two fingers, and judging whether the quality of the fingerprint images reaches the standard or not. According to the two-finger fingerprint verification method, the abnormity of insufficient light source intensity or improper angle is pointedly corrected through secondary adjustment, and the image quality evaluation standard combining the edge sharpness and the effective area proportion provides reliable data support for two-finger fingerprint verification, and the fingerprint verification accuracy and the actual application effect are improved.

The invention discloses an access control method based on artificial intelligence, and relates to the technical field of access control. When the personnel in the monitoring range stay for a preset time length or press a physical key, triggering an access control request, collecting a video frame containing a human face and extracting a human face image; ambient brightness is measured through a photosensitive sensor, illumination compensation is performed before graying is performed when the ambient brightness is lower than a threshold value, and otherwise, graying is performed directly to obtain a grayed face image; identifying the grayed face image by using a local shielding face identification method, if the identification succeeds, acquiring a personnel ID, and if the identification fails, entering a server side for secondary identification; sending the grayed face image to a server, performing secondary recognition through a deep metric learning algorithm, and if the recognition succeeds, obtaining a personnel ID; and fingerprint composite verification: when any end is successfully identified, acquiring a personnel fingerprint image and acquiring a real-time fingerprint, and opening an access control after successful matching. According to the invention, efficient and safe access control is realized through a dual-biological characteristic cooperation mechanism combining face preliminary verification with fingerprint accurate confirmation.

The invention discloses a rapid magnetic resonance fingerprint reconstruction method and system based on K uniform hypergraph regularization, and relates to the technical field of magnetic resonance fingerprint imaging. The invention aims to solve the problems that the imaging quality is reduced due to data undersampling artifacts in magnetic resonance fingerprint imaging at present, and a non-local irregular anatomical structure is difficult to model and the calculation complexity is high in the existing method. The method comprises the following steps: (1) acquiring undersampled magnetic resonance fingerprint data; (2) constructing a K uniform hypergraph; (3) establishing a magnetic resonance fingerprint reconstruction model based on K uniform hypergraph regularization; (4) constructing an iterative solution algorithm based on an incremental sub-gradient approximation method; (5) setting an iterative solution algorithm termination condition; and (6) reconstructing the magnetic resonance fingerprint data and the quantitative parameter image by using an iterative solution algorithm. Experiments show that under the condition of high-power undersampling, a high-quality magnetic resonance fingerprint image can be reconstructed by using less sampling data, the reconstruction time is shortened, and a more reliable quantitative image basis is provided for clinical disease diagnosis and treatment monitoring.

The application provides a lens system, a fingerprint identification device and a terminal device. The lens system comprises: a first lens and a second lens arranged in sequence from an object side to an image side; the first lens is a negative lens, the first lens has a concave surface facing the object side and a convex surface facing the image side, at least one surface of the first lens is aspherical; the second lens is a positive lens, the second lens has a convex surface facing the image side, at least one surface of the second lens is aspherical; the focal length f1 of the first lens and the focal length f2 of the second lens satisfy -5 < f1 / f2 < -2.61. Through the technical scheme, the surface type and the focal length distribution of the two lenses in the lens system are designed, so that the lens system has better imaging quality. Therefore, the lens system has lower cost, lower structural complexity and smaller size while having better imaging quality, which is conducive to the promotion and use of the lens system in the fingerprint imaging device or other imaging device.

The invention discloses a lightweight non-repudiation model fingerprint efficient traceability method, and belongs to the related technical fields of cryptography application, digital content traceability and the like. The method comprises the following specific steps: inputting an original image data set into a computer system; training and learning a lightweight encoder and a decoder, wherein the encoder maps a binary fingerprint and an image to generate a residual error; the residual error is constrained through a Sigmoid function to generate a fingerprint-containing image, and the model is optimized through dual loss; generating metadata of a PIT parameter binding salt value and a commitment value, and embedding the fingerprint into the image; during detection, a decoder is loaded to extract a decoded fingerprint, binaryzation is carried out through a threshold function, and dual verification is realized through fingerprint polynomial comparison and commitment value verification. According to the method, a fingerprint verification mode is converted into polynomial verification through a polynomial equivalent detection technology, the communication complexity is reduced to sub-linear overhead, lightweight efficient verification is realized, and the method is suitable for efficient traceability and authenticity verification of deep forged images.

The invention discloses an under-screen fingerprint module automatic alignment calibration system and method based on sensing feedback, and relates to the field of intelligent electronic equipment manufacturing and optical sensing, and the method comprises the steps that a fingerprint recognition module collects a fingerprint image; the position detection sensor units are arranged on the periphery of the fingerprint identification module and are used for detecting offset data of the fingerprint identification module on the X axis, the Y axis and the Z axis based on a screen trepanning theory center coordinate; the control unit outputs corresponding adjusting instructions according to the offset data, detected by the detection position detection sensor unit, of the fingerprint identification module on the X axis, the Y axis and the Z axis; the fine tuning execution mechanism pushes the fingerprint identification module to move to the theoretical center coordinate position of the screen trepanning in the corresponding direction; the calibration reference module stores theoretical center coordinates of screen trepanning; and the locking mechanism controls the position of the fingerprint identification module to be finally locked when the fine tuning execution mechanism pushes the fingerprint identification module to the theoretical center coordinate position of the screen trepanning. According to the invention, the accuracy, the stability and the production yield of fingerprint identification are improved.

This application discloses a fingerprint retrieval method, apparatus, non-volatile storage medium, and electronic device. The method includes: determining the minutiae distribution and orientation map of a fingerprint image to be retrieved, wherein the minutiae distribution and orientation map represent the distribution and orientation information of the minutiae in the fingerprint image; processing the fingerprint image and the minutiae distribution and orientation map using a fingerprint feature extraction neural network to obtain a feature vector of the fingerprint image to be retrieved, wherein the length of the feature vector is a preset length; and determining a set of candidate fingerprint images in a fingerprint database based on the feature vector. This application solves the technical problem of low fingerprint retrieval efficiency caused by the manual design of feature vectors for fingerprint images in related technologies.

The invention relates to an acquisition method and system supporting fingerprint acquisition at any window position. The method comprises the following steps: acquiring image data on a window; performing image processing on the acquired image data, identifying and positioning a fingerprint area in a window, and judging a dry and wet state of a fingerprint; parameters of acquisition equipment are adjusted according to the identified fingerprint area information and fingerprint dry and wet state information, and the parameters comprise the acquisition position of a CMOS sensor, the size of an acquired image, exposure time, a gain value, light source brightness and the like; the acquisition device acquires a fingerprint image according to the adjusted parameters; and carrying out adaptive contrast enhancement processing based on histogram analysis on the acquired fingerprint image. According to the invention, the fingerprint area position in the window can be identified in real time, and fingerprints can be collected at any window position; meanwhile, the system also has a fingerprint dryness and humidity detection function, optimizes parameters of acquisition equipment in real time, and ensures that the quality of the acquired fingerprint image is always kept at a relatively high level.

The present disclosure provides a fingerprint unlocking method and device and a terminal device, wherein the method is applied to a terminal device, and the method comprises: in response to detecting a fingerprint unlocking instruction, acquiring target environment data of an environment in which the terminal device is located; determining a target exposure time of an optical sensor when collecting a fingerprint image according to the target environment data; controlling the optical sensor to continuously expose for the target exposure time to acquire the fingerprint image; and unlocking the terminal device according to the fingerprint image. The method can dynamically adjust the exposure time according to the environment data to improve the unlocking speed or the unlocking success rate.

The application discloses a control method and device of a dual-fingerprint verification device, the dual-fingerprint verification device and a storage medium, and the method comprises the following steps: when a first fingerprint collection module and a second fingerprint collection module simultaneously collect fingerprint images of the same fingerprint surface of a human finger, acquiring a first fingerprint image and a second fingerprint image; respectively matching and comparing the first fingerprint image and the second fingerprint image with a fingerprint image library; when the first fingerprint image and the second fingerprint image are matched, superimposing and comparing the first fingerprint image and the second fingerprint image; and performing similarity comparison on non-superimposed fingerprint areas in the obtained first fingerprint image and second fingerprint image; and determining whether the first fingerprint image and the second fingerprint image are successfully double-verified according to the similarity comparison result of the superimposed fingerprint area and the non-superimposed fingerprint area. According to the scheme, the dual-fingerprint verification is performed on the fingerprints collected by two different manners at the same time, the single fingerprint collection manner is prevented from being cracked, and the security is improved.

The embodiment of the invention discloses an image generation method, electronic equipment and a computer readable medium. The method comprises the following steps: acquiring an original fingerprint image; editing the original fingerprint image based on the mask image to generate an edited fingerprint image; performing noise addition processing on the edited fingerprint image to generate a noise fingerprint image; and performing denoising processing on the fingerprint image with noise through a pre-trained diffusion model to generate an augmented fingerprint image. According to the embodiment, the authenticity of the augmented fingerprint image is improved.

The invention discloses a wet latent fingerprint identification method and system based on a humidity self-adaptive optical storage device, a terminal and a medium, and the method comprises the steps: obtaining an original wet latent fingerprint image, and converting the original wet latent fingerprint image into an ultraviolet pulse sequence adaptive to the optical response characteristics of the humidity self-adaptive optical storage device; a reservoir array is built based on a humidity self-adaptive optical storage device, an ultraviolet light pulse sequence is received based on the reservoir array, and a current amplitude signal matched with a corresponding pixel fingerprint feature is output based on humidity adjustable and self-adaptive characteristics of the humidity self-adaptive optical storage device. Outputting a feature vector bearing the core feature of the wet latent fingerprint based on the current amplitude signal; and inputting the feature vector into a neural network for fingerprint identification, and outputting a fingerprint identification result based on a readout layer of the neural network. According to the invention, the core problems of low identification precision in a high-humidity environment, high delay of a traditional system and high energy consumption are effectively solved, and the efficiency and reliability of wet latent fingerprint identification are remarkably improved.

An electronic device is provided. The electronic device includes a fingerprint sensor, a camera, and a processor operatively coupled to the fingerprint sensor and the camera. The processor may be configured to determine whether a plurality of biometric authentications are being performed when an input for performing user authentication is detected through the fingerprint sensor, stop user authentication using the camera if it is determined that the plurality of biometric authentications are being performed, and perform user authentication if a fingerprint image acquired through the fingerprint sensor matches a previously registered fingerprint image.

Embodiments of the present application relate to a fingerprint matching method and device, computer equipment and a storage medium, comprising: obtaining a first fingerprint image to be matched; expanding the first fingerprint image to generate an expanded second fingerprint image; performing fingerprint matching based on the first fingerprint image and the second fingerprint image to obtain a target matching fingerprint image corresponding to the first fingerprint image. Thus, by using the fingerprint latent distribution rule, the small-area fingerprint can be expanded, and the recognition rate of the small-area fingerprint can be improved.

The invention provides a fingerprint detection method and device. The fingerprint detection method comprises the following steps: acquiring a fingerprint image through a fingerprint sensor; determining a first score of the fingerprint image based on a first fingerprint detection mode; determining a second score of the fingerprint image based on a second fingerprint detection mode and the first score in response to the first score exceeding a first threshold value; and determining a fingerprint detection result based on the first score and the second score, thereby improving generalization and accuracy of fingerprint detection without adding extra hardware.

The invention relates to a fault detection method and device, computer equipment, a computer readable storage medium and a computer program product. The method comprises the following steps: acquiring an analog voltage signal; the analog voltage signal is generated by performing corresponding XOR operation on the linear feedback shift register module; amplifying and coupling the analog voltage signal, and injecting the amplified and coupled analog voltage signal into a reactor to be tested; acquiring a response voltage signal and a response current signal of the to-be-tested reactor to the analog voltage signal; extracting multi-domain features from the response voltage signal and the response current signal, and coding based on the multi-domain features to obtain a feature fingerprint image; and inputting the feature fingerprint image into a fault identification model to obtain a fault identification result. By adopting the method, the fault type can be identified in time.

A method of fingerprint verification includes capturing a fingerprint image by an image sensing device. The image sensing device including a pixel array of a combination of sensing pixels configured to capture minutia points in the fingerprint image and positioning pixels configured to provide positioning codes. The method further includes calculating vectors of the minutia points with reference to the positioning codes, comparing the vectors to reference vectors generated from a reference fingerprint image, and determining a match between the fingerprint image and the reference fingerprint image based on the comparing of the vectors.

The application discloses a dynamic environment robust indoor positioning method based on multi-source unsupervised domain adaptation, and relates to the technical fields of wireless communication and indoor positioning. The method of the application firstly pre-processes collected channel state information to construct a fingerprint image; then utilizes a multi-source unsupervised domain adaptation framework to integrate historical data knowledge from multiple time scales through a two-stage alignment strategy (feature distribution alignment and regressor output alignment), learn domain-invariant features, and reduce the dependence on labeled data of the target domain; and adopts a feature learning backbone network integrated with multi-scale convolution, multi-scale channel attention mechanism and attention feature fusion to extract features robust to environmental changes. The application can realize high-precision and high-robustness positioning in a dynamic indoor environment, and effectively overcome the defects of traditional methods caused by distribution drift.

The display screen, the fingerprint image acquisition method and the display device are provided, and the display screen comprises a substrate, a photosensitive element arranged on one side of the substrate, a pixel definition layer and a light-emitting layer, the pixel definition layer is arranged on a side of the photosensitive element away from the substrate, the pixel definition layer has a plurality of pixel openings, and the light-emitting layer is arranged at the pixel openings, a color film layer comprising a target color filter unit and a black matrix, the black matrix opposite to the photosensitive element is provided with an imaging hole, and a light-blocking structure is located between the photosensitive element and the target color filter unit and is configured to block a transmission path of target light between the target color filter unit and the photosensitive element, wherein the target light is ambient light passing through a fingerprint of a user's finger when the finger touches a fingerprint recognition area of the display screen.

The present application relates to a kind of fingerprint identification methods, residual fingerprint or spot fingerprint in fingerprint image, press deeper \ wet finger fingerprint, normal fingerprint identification can be realized, can improve identification accuracy, the method is based on fingerprint instrument system implementation, fingerprint instrument system includes fingerprint collection module, data processor, prompt module, the steps of processing, identifying to fingerprint image include: obtaining fingerprint image;Fingerprint image is preprocessed;The preprocessed image is blocked, obtains image block, calculates the gray mean and gray variance of each image block;Determine whether the fingerprint image is abnormal image or normal image;Determine whether the deep gray region in fingerprint image is pressed deeper \ wet finger fingerprint or spot map;The foreground region in fingerprint image is invalid fingerprint or normal fingerprint, if it is normal fingerprint or press deeper \ wet finger fingerprint, then through prompt module sends prompt, program stops, if it is invalid fingerprint, then prompt module does not send prompt.

This invention discloses a method for supporting individual educational development based on innate biometric assessment. The method first collects fingerprint image data, which is considered lifelong and unchanging, from individuals. Second, it preprocesses the fingerprint images and extracts quantified feature vectors. Then, it inputs these feature vectors into a pre-trained biometric-educational trait association model to obtain quantified assessment scores for the individual across multiple preset educational trait dimensions. Next, combining the assessment scores, individual age, and developmental goals, a personalized initial educational development plan is generated by matching rules through an educational plan generation rule engine. This invention uses stable biometrics as an objective benchmark and, through a computable model and rule engine, achieves a complete technical process from innate trait assessment to the generation and optimization of long-term, dynamic, and personalized educational support plans, solving the technical problems of traditional methods that rely on unstable acquired assessments and lack a long-term reference system.

The invention discloses a fingerprint image processing method, a fingerprint lock and electronic equipment. The method comprises the following steps: adjusting parameters of at least two cameras to perform fingerprint image acquisition based on the at least two cameras to obtain a plurality of fingerprint multi-shot image groups including fingerprint shot image sequences acquired by the cameras; extracting a first fingerprint feature of the fingerprint multi-shot image group, and screening the fingerprint multi-shot image group according to a quality score of the first fingerprint feature to obtain a preferred fingerprint multi-shot image group; extracting a second fingerprint feature from a fingerprint image in the preferable fingerprint multi-camera image group, and obtaining depth information according to the parameter and an image parallax between the at least two cameras; according to the depth information, aligning the second fingerprint feature of the corresponding fingerprint image in the preferable fingerprint multi-shot image group to obtain an enhanced fingerprint image; and performing fingerprint identification according to the enhanced fingerprint image. According to the invention, the accuracy of fingerprint identification can be improved.

Disclosed is a display device including a display unit displaying an image, a fingerprint sensing unit arranged at one side of the display unit and including a fingerprint sensing pixel for sensing a fingerprint, and a reading circuit receiving a fingerprint sensing signal from the fingerprint sensing pixel, wherein the reading circuit generates a normal fingerprint image and a dry fingerprint image corresponding to the fingerprint sensing signal during a fingerprint enrollment mode.

The utility model provides a fingerprint acquisition device, relates to the technical field of fingerprint identification, and aims to solve the problem of mistaken touch in fingerprint identification. The fingerprint acquisition device comprises a switch and a fingerprint module, the switch comprises a first switch and / or a second switch, the first switch is electrically connected between a pressure-sensitive device and the fingerprint module, and the second switch is electrically connected between the pressure-sensitive device and a processor of the electronic equipment. The capacitance of the pressure-sensitive device changes along with the magnitude of the pressure borne by the pressure-sensitive device; the fingerprint module is electrically connected with a processor of the electronic equipment, and the fingerprint module comprises a pressure detection module and a fingerprint acquisition module; the pressure detection module generates an electric signal corresponding to pressure when a finger touches the fingerprint module, and the fingerprint acquisition module is used for acquiring a fingerprint image.

This application provides a training method for a fingerprint recognition network, a fingerprint recognition method, an apparatus, and a medium. The training method for the fingerprint recognition network includes: determining fingerprint feature matching maps based on a first initial fingerprint image and a second initial fingerprint image; forming a training sample set from multiple fingerprint feature matching maps; and training an original neural network based on the training sample set to obtain a fingerprint recognition network. The technical solution provided by this application solves the problem of difficulty in distinguishing whether two different fingerprint images belong to the same finger, thus reducing the false acceptance and false recognition rates of fingerprint recognition.

The application relates to a user release method and device, computer equipment and a storage medium. The method comprises the following steps: acquiring a first fingerprint image, a first face image and a first voice signal of a first user; determining the quality scores of the first fingerprint image, the first face image and the first voice signal respectively, so as to determine the first weight of the first fingerprint image, the second weight of the first face image and the third weight of the first voice signal respectively; determining the first similarity between the first fingerprint image and a second fingerprint image of a second user, the second similarity between the first face image and a second face image of the second user, and the third similarity between the first voice signal and a second voice signal of the second user; and determining the release result for the first user based on the first weight, the first similarity, the second weight, the second similarity, the third weight and the third similarity. The method can improve the identity verification accuracy for the first user.