76 results about "Palm print" patented technology

The invention discloses a novel graph contrast learning framework with mutual information maximization, and relates to the technical field of graph contrast learning, multi-modal learning and mutual information maximization. The framework comprises the following steps: constructing a nearest neighbor graph, spreading similar samples to data of a missing mode, optimizing a loss function, and performing clustering optimization. The existing method has two main problems: (1) the existing method is mostly suitable for complete data and has a poor processing effect on data of a missing mode; and (2) the current palmprint and palm vein fusion recognition technology does not completely capture the complex relationship between the palmprint and palm vein features, resulting in inaccurate clustering result. According to the method, the modal loss in the incomplete palm print and palm vein fusion recognition task is effectively reduced, and the clustering performance is enhanced. According to the method, the mutual information maximization loss function is introduced, the adaptability and robustness of the model to incomplete data are effectively enhanced, and the method has high recognition precision and clustering performance when processing incomplete multi-modal data.

Certain biometric authentication and verification methods use multiple biometric modalities of a given user in order to enhance their security. Circumvention of such methods sometimes involves presenting multiple biometrics as if they come from a single user when, in fact, they arise from more than one person. To thwart such attacks, it is necessary to bind multiple biometric modalities to each other. One binding method captures physiological signals of a user, such as pulse rate, in conjunction with the capture of each biometric. When the physiological signals associated with each of the biometric modalities match, the biometrics are bound. Another binding method captures an intermediate biometric when capturing each of the multiple biometric modalities. When the intermediate biometrics match, the multiple biometric modalities are bound. For example, for face and finger biometrics, a palm intermediate biometric may be used.

1. The name of the design product: the terminal device of the ladder control. 2. The use of the design product: used in the elevator, identify face, palm print, two-dimensional code, IC card access permission and display relevant state information. 3. The design points of the design product: in shape. 4. The picture or photo that can best show the design points: front view.

1. The name of the design product: biometric identification device. 2. The use of the design product: can identify palm vein, palm print and other information, carry out identity recognition and information acquisition, and is used in the fields of payment and access control identity recognition. 3. The design points of the design product: in shape. 4. The picture or photo that best indicates the design points: perspective view 1.

The invention relates to the technical field of data processing, in particular to an article deposit management system based on the Internet of Things, which comprises a data acquisition module, an authentication deposit module, a deposit space distribution module and a deposit environment sensing module. The system manages the locker subsequently, authenticates the identity of the user through the authentication and storage module, realizes high-precision identification according to double authentication of the iris and palmprint of the user, and adjusts the double authentication through environment information to realize high-precision identification. The storage space of the storage cabinet is intelligently distributed through the storage space distribution module, the distribution of the storage cabinet space is precisely corrected through the storage environment sensing module, the situation that the storage space is unreasonably utilized is avoided, it is guaranteed that a user obtains a proper storage environment for storing articles, and reasonable distribution of the storage space is achieved.

This application provides a method for determining an artificial palm print generation model performed by a computer device. The method includes: performing data augmentation on a first real palm print image of a first user to obtain a data-augmented first real palm print image; obtaining a first artificial palm print image corresponding to the first user using a deep learning model using the data-augmented first real palm print image and a first identity control curve of the first user; adjusting, when a degree of similarity between the data-augmented first artificial palm print image and the data-augmented first real palm print image is not less than a preset similarity threshold, parameters of the deep learning model; and determining, when the degree of similarity thereof is less than the similarity threshold, the deep learning model as the artificial palm print generation model.

A biometric recognition device for palm prints and palm veins includes: a light source being used to emit illuminating beams in a near-infrared band; a polarizing unit being used to convert the illuminating beams to polarized beams which are emitted to a palm; an imaging unit receiving retroreflected beams from a palm and being used to converge the retroreflected beams to a focal plane; a polarizing beam splitter forming transmitted beams and reflected beams based on different polarization directions of beams from the imaging unit, wherein the transmitted beams propagate after pass through the polarizing beam splitter, and the reflected beams propagate after reflected by the polarizing beam splitter. An identity authentication method is further provided. Based on the non-contact technical solution, only one light source is used to obtain the palm print images and palm vein images at the same time and in the same space.

The invention discloses a palm biological feature fusion recognition method and device, a storage medium and equipment, and belongs to the field of biological feature recognition. According to the method, the characteristic that the distribution positions of the palm print main line and the palm vein blood vessels are relatively fixed is utilized, the intersection points of the palm print main line and the palm vein blood vessels serve as the feature points, the feature point set used for registration and recognition is constructed, feature-level fusion of the palm prints and the palm veins is achieved, and comparison is conducted through the fused feature point set, so that the registration accuracy is improved. Therefore, palm biological feature fusion recognition is realized. According to the method, the advantages that the palmprint principal line for palmprint recognition is thicker, obvious and stable in feature and not prone to interference compared with other features, the blood vessel near-infrared imaging for palmprint vein recognition is hidden and not prone to interference, and the advantages of correlation and dependence of relative position distribution of palmprint and palmprint vein are combined, so that the accuracy of palmprint and palmprint vein recognition is improved, and the accuracy of palmprint and palmprint vein recognition is improved. The recognition precision and the recognition reliability of biological characteristics are greatly improved, and accurate recognition of palm prints and palm veins is achieved.

Provided herein are systems and methods for authenticating a customer for a completing different types of restricted transactions. More specifically, provided herein are biometric authentication systems and processes for completing transactions where the goods and services at issue are subject to one or more transaction conditions, such as age-related restrictions. The systems described herein involve a point-of-interaction device that facilitates biometric authentication by obtaining and verifying an individual's biometric information, such as fingerprints, palm prints, or facial scans. This biometric data is then used to determine whether the individual meets the necessary conditions for the restricted transaction, such as age verification. The system aims to enhance security and efficiency in transactions by eliminating the need for physical cards and reducing the risk of fraud.

The application provides a vehicle-mounted network security authentication method and system, comprising: in response to a user's OTA upgrade operation, sending an upgrade request for a vehicle end to a cloud; receiving a quantum key generated by the cloud in response to the upgrade request based on a quantum communication channel; collecting real-time palmprint information of the user, and generating a dynamic key based on dynamic characteristics of the real-time palmprint information; combining the dynamic key with the quantum key and generating a fused quantum key, encrypting and digitally signing an upgrade data packet based on the fused quantum key, and sending the encrypted upgrade data packet to the cloud for verification of the digital signature; in response to an authorization instruction sent from the cloud that the digital signature verification is passed, decrypting the upgrade data packet based on the quantum key and the dynamic key, and performing the OTA upgrade operation. The non-reproducibility of the fused quantum key and the uniqueness of the dynamic key eliminate the possibility of key cracking, and improve the security of vehicle-mounted software during the OTA upgrade process.

1. Name of the product in this design: Multimodal Biometric Device. 2. Purpose of this design: This design is a multimodal biometric identification device, which is installed on various pedestrian access gates to identify pedestrians through facial recognition, palm print, card swiping, and other methods. 3. The key design feature of this product is its shape. 4. The picture or photo that best illustrates the key design points: Design 1 3D diagram 1. 5. Design 1 is designated as the basic design.

The present application relates to the field of palm print-based payment, and discloses a palm print acquisition method and apparatus, a device, and a storage medium. The apparatus comprises conveying belts that are arranged in a crisscross manner, and a supporting frame; a palm print acquisition assembly is fixedly mounted at the center of the transverse conveying belt; a belt body of the transverse conveying belt is sleeved in a first slide groove, and the first slide groove is fixedly mounted on the longitudinal conveying belt; a belt body of the longitudinal conveying belt is sleeved in a second slide groove, and the second slide groove is fixedly mounted on the supporting frame; the transverse conveying belt and the longitudinal conveying belt are respectively controlled by a first stepper motor and a second stepper motor to realize transverse and longitudinal sliding. The apparatus can identify an acquired palm shape, and determine a palm orientation and a palm deflection angle on the basis of the palm integrity and key points. For leftward or rightward deviation of a palm, an aperture can be moved to a position directly facing the center of the palm by leftward or rightward moving the transverse conveying belt of the apparatus. For upward or downward deviation of the palm, the aperture is moved to the position directly facing the center of the palm by upward or downward moving the longitudinal conveying belt of the apparatus.

The invention relates to a method for rapidly extracting palm vein information from a palm print image, and belongs to the technical field of vein recognition and information security, and the method comprises the following steps: collecting the palm print image through a mobile terminal, converting the palm print image into an RGB data format, and then carrying out adaptive adjustment; carrying out filtering processing on the RGB three-channel image of the palmprint image after adaptive adjustment; extracting palmprint features, and performing feature fusion by using the palmprint features of the palmprint image in the R, G and B channels to obtain palmprint fusion features in the palmprint image; the palm vein information is extracted based on the palm print fusion features in the palm print image, the palm vein technology can be directly applied to the mobile terminal equipment, the similarity between the palm vein image and the palm vein image collected by a professional palm vein image collector is larger than 99%, the palm vein information is quite accurate, the accuracy of identity recognition is improved, and the user experience is improved. And the false identification rate is reduced.

The invention discloses a palm plane image acquisition method and device, electronic equipment and a medium, and relates to the technical field of image acquisition, and the method comprises the steps: obtaining a plurality of distance parameters between a palm plane and a camera, and determining a comprehensive distance value of the palm plane relative to the camera according to the plurality of distance parameters; determining a light supplementing strategy of the palm plane according to the comprehensive distance value; acquiring a palm plane image shot by the camera under the light supplementing strategy and a quality parameter of the palm plane image; and when the quality parameter of the palm plane image is smaller than a preset quality parameter, adjusting a shutter parameter of the camera, so that the quality parameter of the palm plane image is greater than or equal to the preset quality parameter. By adopting the method, the light supplement strategy can be adaptively adjusted under different conditions to obtain a palm plane image with uniform brightness and clear details, so that the imaging quality and recognition accuracy of palm vein features and palm print features are improved.

The embodiment of the invention relates to the technical field of biological recognition, and discloses a palm print and palm vein bimodal recognition method and electronic equipment. According to the method, the quality weighted fusion is performed on the plurality of palm print images of the same palm, the fused palm print feature vector with higher robustness is generated, and the process can adaptively improve the contribution of the high-quality image and suppress the interference of the low-quality image; synchronously acquiring corresponding palm vein images and extracting feature vectors of the palm vein images; and a progressive identification strategy is adopted, rapid preliminary screening is performed by using the fused palmprint features so as to reduce the identification range, and then a preliminary screening result is accurately authenticated in combination with the palmprint vein features with higher anti-falsification. According to the method, the quality sensitivity defect of palmprint recognition is effectively overcome through a quality adaptive fusion mechanism, the complementary advantage of bimodal is fully played, and the accuracy, stability and safety of identity recognition in a complex actual scene are remarkably improved.

A portable biological information collection all-in-one machine, comprising a box body, a first folding cover and a second folding cover, the box body is provided with a high-speed scanner, a two-dimensional code and certificate identification module, a palm print collection module, a camera module, a first display screen and an iris collector; wherein the box body is further provided with a first face and a second face arranged oppositely and a first storage bin for placing the iris collector, the high-speed scanner, the two-dimensional code and certificate identification module, the palm print collection module and the camera module are arranged on the second face, the first display screen is arranged on the first face, and the opening of the first storage bin is arranged on the side surface of the box body between the first face and the second face; the first folding cover and the second folding cover are respectively connected to the first face and the second face and can be rotatably stored on the box body to protect the box body. The present scheme adopts a modular integrated structure design, which achieves the effects of reducing the overall volume of the portable biological information collection all-in-one machine, enhancing the convenience of carrying and operating the portable biological information collection all-in-one machine and improving the work efficiency of the staff.

The invention belongs to the technical field of biological recognition, and relates to a multi-modal feature fusion method and system based on deep learning, and the method comprises the steps: obtaining preprocessed biological feature images of different modalities, the different modalities including an iris, a face, a fingerprint, a palm print and a voiceprint; constructing feature extraction networks of different modes based on deep learning; inputting the biological feature images of different modes into a feature extraction network of a corresponding mode to obtain biological features in different modes; the biological characteristics in different modes are arranged and spliced according to a dimension descending order, and multi-mode biological characteristics are obtained; constructing a multi-modal biological feature fusion network based on deep learning; pre-processing the multi-modal biological characteristics, and inputting the pre-processed multi-modal biological characteristics into a multi-modal biological characteristic fusion network to obtain multi-modal fusion characteristics. The method has the beneficial effects that after the biological characteristics of different modes are compressed, the characteristic dimension is reduced, and high-speed and high-precision biological characteristic comparison is realized.

This application discloses a control method and device for a vehicle tailgate, a storage medium, an electronic device, and a computer program product, relating to the field of vehicle control. The control method for the vehicle tailgate includes: acquiring a palm image of a target object; performing correction processing on the palm image to adjust it to a standard posture; using a pre-trained detection model to detect the palm image to obtain a palmprint image; extracting feature information from the palmprint image; and controlling the opening of the vehicle tailgate by correcting the posture of the palmprint image to ensure that the palmprint image can reach a standardized posture, thereby improving the accuracy of subsequent palmprint recognition and comparison, and improving the accuracy of vehicle tailgate control.

This application discloses an identity verification method and system, belonging to the field of identity verification technology. The method includes: if the palm to be identified is detected to be within a preset recognition range, sending a first supplementary light command to a first supplementary light component and a second supplementary light component; sending a first image acquisition command to a first image acquisition device and a second image acquisition device; receiving a palm shape image and a palm print image sent by the first image acquisition device, and a palm vein image sent by the second image acquisition device; acquiring palm shape features, palm print features, and palm vein features corresponding to the palm to be identified based on the palm shape image, palm print image, and palm vein image, respectively; acquiring fusion features corresponding to the palm to be identified based on the palm shape features, palm print features, and palm vein features, and acquiring the identity recognition result corresponding to the palm to be identified based on the fusion features.

1. The name of the design product: multifunctional palm print identification payment terminal (PP01). 2. The use of the design product: the design product is used for a multifunctional palm print identification payment terminal. 3. The design points of the design product: in shape. 4. The picture or photo that best indicates the design points: perspective view 1.

The application relates to a palmprint image expansion method based on a multi-connection generative adversarial network, and specifically comprises the following steps: acquiring a real palmprint image and an initial generative adversarial network; mapping random generated noise into a real palmprint image feature space through an image generator to obtain a generated palmprint image; judging a difference value of the real palmprint image and the generated palmprint image through an image discriminator; optimizing and training the image discriminator and the image generator according to the difference value to obtain a trained generative adversarial network; and expanding the palmprint image according to the trained generative adversarial network. In the whole process, the palmprint image is generated based on the random generated noise, and the generative adversarial network is optimized and trained based on the difference between the real palmprint image and the generated palmprint image, so that the finally obtained trained generative adversarial network can realize effective expansion of the palmprint image, thereby supporting training of a palmprint recognition model of a small sample palmprint image.

The application discloses a kind of non-contact palm vein multi-modal identification system based on deep learning, including multi-modal image acquisition and processing terminal, mode matching and identification decision terminal, security protection and anti-fake terminal, iterative optimization terminal;Multi-modal image acquisition and processing terminal are used to collect palm print and palm vein image, carry out dynamic calibration, image quality enhancement and pre-processing, output multi-modal image;Mode matching and identification decision terminal are used to carry out feature extraction, multi-modal feature fusion, mode matching and identification decision, and output final matching result;Security protection and anti-fake terminal are used to carry out living body detection, anti-fake monitoring, data encryption;Iterative optimization terminal is used to realize model light weight, knowledge distillation, end-to-end optimization and continuous learning.The application improves the recognition accuracy and environmental adaptability under complex state by deformation invariant feature extraction and cross-modal attention fusion.

The invention discloses a palm print and palm vein camera evaluation method based on a deep neural network. The method comprises the following steps: constructing a palm print and palm vein imaging camera quality evaluation interface; collecting a palm print and palm vein image, generating a palm print and palm vein region of interest by using a HandLandmarker model, and preprocessing the palm print and palm vein region of interest to obtain a preprocessed image; inputting the preprocessed image into an improved MobileFace model to construct a standard feature vector library, and obtaining a to-be-detected feature vector; performing similarity calculation on the to-be-measured feature vector and a standard feature vector library to generate an imaging quality evaluation conclusion; the evaluation information is displayed on an evaluation interface, and an evaluation log is generated; and executing abnormal detection of image blurring, insufficient number of palm key points, model loading failure and camera connection failure. According to the method, automatic and standardized evaluation of the quality of the palm print and palm vein imaging camera is realized, and the method can be used for production detection and quality control scenes of palm print and palm vein recognition equipment.

The invention relates to the technical field of biological feature recognition and in-vivo detection, in particular to a dynamic palm print and palm vein bimodal decision fusion in-vivo detection method and system.The method comprises the steps that palm key points in a video stream are dynamically collected and detected in real time, a backbone network of an improved AG-FAS model is utilized, and the dynamic palm print and palm vein bimodal decision fusion in-vivo detection is obtained; extracting palm living body characteristics from the input multi-condition fused palm print and palm vein image data set through transfer learning, and outputting palm living body characteristic data; respectively utilizing two independent detection models, namely a palm print living body model and a palm vein living body model, to obtain corresponding authenticity confidence; and performing fusion judgment based on the confidence coefficients of the two independent models to obtain a judgment result. By applying the method, the accuracy, the robustness and the generalization of living palm detection can be remarkably improved.

Disclosed are an illumination system and a palm scanning device. The illumination system is used in the palm scanning device, and the illumination system includes an illuminating lamp and a DMD reflector. The DMD reflector is located on an emergent light path of the illuminating lamp. The DMD reflector includes a plurality of pixel reflectors, and angles of the plurality of pixel reflectors are adjustable, to cause a field of view (FOV) of reflected light of the DMD reflector to be adjustable.

The invention relates to the technical field of data analysis, in particular to a palmprint recognition anti-fraud method based on double-branch self-supervised learning, and the method comprises the steps: constructing a double-branch self-supervised reconstruction architecture, determining a first to-be-processed image based on a high-frequency self-supervised branch, and determining a second to-be-processed image based on a chromaticity regularization self-supervised branch. Dividing the two images into patch blocks which are not overlapped with each other, independently generating random mask matrixes with different spatial distributions, determining visible areas, inputting the patch blocks of the visible areas into a shared encoder for feature extraction, outputting latent variable features, and splicing the latent variable features with learnable mask marks to obtain a patch matrix; and respectively sending to a high-frequency decoder and a chroma decoder, determining total loss, carrying out physical decoupling on illumination and material attributes, and carrying out fine adjustment on the architecture to finish convergence of the architecture. According to the method, the palm print features with discrimination are extracted through the shared encoder, and chromaticity distribution consistency constraints are introduced, so that effective decoupling of ambient light and real material attributes is realized.

The present application relates to the technical field of image processing and analysis, and particularly relates to a dynamic palmprint ROI recognition method and system based on video, which comprises the following steps: acquiring a video frame containing a user's palm; selecting a video frame containing a palm and having a palm boundary as an effective frame; selecting an effective frame meeting image condition requirements as a key frame; extracting a palm ROI and palmprint features; registering the palmprint; matching the user's palmprint features with registered palmprints to perform palmprint recognition. The present application can improve the flexibility of image shooting by acquiring a palm video image, screening key frames therefrom, effectively avoiding problems such as focus blur caused by movement, improving the efficiency of palmprint collection by frame-by-frame screening, obtaining more abundant information from dynamic video data or continuous multiple frames of images, being conducive to feature extraction and identification, and improving the convenience and practicality of palmprint recognition on the premise of retaining abundant image information.

This application discloses a power consumption control method, device, and storage medium for palmprint recognition, used to reduce the continuous working time of the palmprint module and lower system power consumption. The method includes: starting a microcontroller unit (MCU) and entering a low-power detection mode, with the palmprint module controlled by the MCU in a sleep mode; initiating a proximity signal detection operation, whereby when an object is detected entering a preset sensing range for a duration exceeding a set time, the MCU controls the palmprint module to switch to a working mode to control the palmprint module to acquire images; performing identity recognition based on the images acquired by the palmprint module and outputting the recognition result; after a preset delay time, re-initiating the proximity signal detection operation, whereby if no object exists within the preset sensing range or the duration of the existing object does not exceed the set time, the MCU controls the palmprint module to switch back to sleep mode, and no proximity signal detection operation is initiated within the preset delay time.

This application discloses a business service method and related equipment. When a business service provider initiates a palmprint business binding program, the method determines the service link information of the target business service to be bound based on the palmprint business binding program; collects the target palmprint information of the business service provider; and establishes and stores a mapping relationship between the target palmprint information and the service link information of the target business service. When the client corresponding to the target object recognizes the target palmprint information of the business service provider, the method provides the target business service to the target object based on the mapping relationship. This application can reduce material costs and avoid resource waste; it helps improve the efficiency and effectiveness of merchants' digital business service operations. Furthermore, it enriches the forms of obtaining business services and helps increase user attention to related services.