277 results about "Palm vein" patented technology

The invention provides a palm vein feature extraction and depth adaptive matching method, which relates to the technical field of biological recognition, and is characterized in that a three-dimensional space-time convolutional neural network and a graph neural network are combined to extract space depth features, time blood flow dynamic features and blood vessel topological features of palm veins, and information bottleneck is utilized to optimize and screen a feature subset with the most distinguishing property; the method breaks through the limitation of traditional two-dimensional texture feature extraction, obtains abundant palm vein information through multi-source data acquisition (such as near-infrared imaging, a light field camera and a spectrum sensor), overcomes the interference of environmental factors such as illumination, angle and noise, achieves the high-precision modeling and stable extraction effects of palm vein features, and can achieve the real-time extraction of the palm vein features in a complex scene. A high recognition rate is kept under different illumination conditions or user hand posture changes, the robustness of the palm vein recognition system is remarkably improved, and the method is suitable for scenes with high safety requirements.

The invention relates to the technical field of attendance management, and discloses an electronic class board attendance system for palm vein recognition, which comprises a palm vein data acquisition module for irradiating the palm of a user through a near-infrared light source and acquiring a palm vein image; the image optimization processing module is used for performing optical modeling optimization, noise removal and quality enhancement on the acquired palm vein image; the deep learning recognition module is used for extracting palm vein features and performing identity matching; the attendance record storage module is used for storing and managing user attendance data; and the control and communication module is used for managing cooperative work of all the modules and performing data interaction with an external attendance database. Through the technical scheme of combining near-infrared illumination and the light transmission equation, the palm vein feature image is accurately extracted, the effect of optimizing palm vein contrast and detail definition is achieved, the problems of palm vein feature edge blurring and detail loss are solved, and the image processing quality is improved.

The present disclosure relates to a desktop safety box including a housing, a cover, a locking device, and a palm vein unlocking module. The housing defines an accommodating cavity and an opening communicated with each other. The cover is mounted on the housing and is capable of opening or closing the opening. When the locking device is in a closed state, a relative position between the cover and the housing is locked, and the opening is closed. When the locking device is in an unlocked state, a lock between the cover and the housing is released, and the opening is allowed to be opened. The palm vein unlocking module is mounted on the housing, electrically connected to the locking device, and configured to acquire palm vein information and drive the locking device to switch to the unlocked state.

In various examples, infrared image data may be used to detect a subcutaneous characteristic(s) (e.g., a palm vein topology) of a person (e.g., a person requesting entry to a vehicle, a vehicle occupant) and authenticate the user based on the detected subcutaneous characteristic(s). For example, infrared image data representing one or more acquired subcutaneous characteristics (e.g., a topology of veins and / or other blood vessels in a region of the authenticating user's palm, hand, neck, forearm, face, fingertip, eye, etc.) may be generated. Hand and / or palm detection may be applied to detect a region depicting the user's hand or palm, and that region (or some subset thereof) may be segmented to generate a representation of an acquired vein topology. The acquired vein topology may be compared with one or more reference vein topologies stored in a database to determine whether the acquired vein topology matches one of the reference vein topologies.

The invention provides a non-contact palm vein anti-attack method based on a lightweight network, and the method comprises the steps: obtaining a palm vein data set, and dividing the palm vein data set into a training data set and a test data set; constructing a lightweight palm vein anti-attack network; the lightweight palm vein anti-attack network is trained; and identifying the palm vein image by using the trained lightweight palm vein anti-attack network. According to the method, the recognition accuracy is 99.6% or above, the average detection time is 8 ms, the model size is 353 kb, the method is easy to deploy under low-computing-power embedded equipment, and real-time, rapid and efficient non-contact palm vein living body detection is achieved; according to the invention, the in-vivo detection of the input palm vein image is realized through the deep learning network, so as to prevent the palm vein image from being attacked and cheated by artificial prostheses.

The invention discloses a subway track automatic ticket checking method and an automatic ticket checking device thereof. The method specifically comprises the following steps: S1, feature acquisition; s2, performing feature fusion; s3, performing anomaly detection; the invention relates to the technical field of subway track automatic ticket checking. According to the subway track automatic ticket checking method and the automatic ticket checking device thereof, through cooperation of palm vein and gait recognition and a non-contact collection mode, the safety of a ticket checking system is improved, the false recognition rate is reduced, meanwhile, the accuracy of abnormal behavior detection is effectively improved, the self-learning ability is provided through a reinforcement learning algorithm, and the accuracy of ticket checking is improved. The ticket checking strategy can be automatically adjusted according to the real-time passenger flow and the operation state, optimal configuration multi-mode identification of resources is achieved, efficiency and safety are balanced, the crowding degree in the peak period can be reduced, and high-satisfaction travel experience is provided for passengers.

The utility model relates to the technical field of medical authentication cabinet machines, in particular to a medical insurance and social insurance self-service authentication cabinet machine based on palm vein recognition, which comprises an authentication cabinet machine body, and a touch display screen used for inquiry is installed on the outer surface of the authentication cabinet machine body. An identity authentication recognition device and a palm vein recognition device are installed on the outer surface of the authentication cabinet body, a positioning plate capable of stretching and rebounding is installed outside the palm vein recognition device, and a stretching assembly used for stretching is installed at the bottom of the positioning plate. When the positioning plate is pressed downwards, the buffer spring connected with the bottom of the positioning plate contracts, and when the sliding block moves downwards to the bottom of the inner wall of the sliding groove together, the positioning plate does not move downwards any more, namely, the distance between the palm placed on the surface positioning plate and the palm vein recognition device is proper, and the purposes of limiting stretching and retracting of the positioning plate and positioning of the palm vein recognition device are achieved. A user can conveniently control the palm placing position and distance, and the success rate of palm vein recognition is increased.

The invention discloses a palm vein image generation method and device, a storage medium and electronic equipment, and relates to the technical field of information. The method comprises the steps that an initial noise image, the number of diffusion steps and condition control information are obtained, and the condition control information comprises an individual identity label, palm posture information used for simulating a real scene and illumination information; generating a condition control embedding vector according to the condition control information; the initial noise image, the diffusion step number and the condition control embedding vector are input into a preset diffusion model to predict noise corresponding to each time step, and the preset diffusion model comprises a linear layer, a cross attention layer and a multi-scale feature layer; and according to the predicted noise corresponding to each time step, gradually updating the image, and finally outputting a target palm vein image under the condition control information. According to the method and the device, the generated palm vein image data can be fit to various complex real scenes, so that the diversity and the practicability of the palm vein image data can be ensured.

The invention relates to the field of identity authentication, in particular to an identity authentication method and system based on palm veins. An identity authentication system based on palm veins comprises an identity information acquisition module, a palm vein image acquisition module, an environment data acquisition module, a feature extraction module, a matching value calculation module, an authentication threshold adjustment module and an identity authentication module. According to the method, the multi-angle fusion operation is executed in the palm vein feature extraction process, so that the image used for executing feature extraction can fit the registered palm vein image, the difference caused by user operation behaviors during identity authentication is avoided, and the false alarm rate during identity authentication is reduced; when the matching value is calculated, the direct distance between the palm vein feature vector of the user and the authenticated palm vein feature vector corresponding to the identity information of the user in the identity library is calculated, and the accumulated distance caused by the change of the operation behavior of the user is also considered, so that the influence of the change of the operation behavior is weakened, and the false alarm rate in actual use is reduced.

The invention relates to an access control attendance system and an access control attendance method based on biological recognition, which solve the problems of accuracy and reliability of identity recognition through a palm print and palm vein recognition technology and effectively avoid potential safety hazards caused by identity misjudgment. And the national secret CPU unit prevents data transmission from being stolen or tampered in a data transmission process through dynamic password authentication and an encrypted communication protocol, so that the safety of the access control system is guaranteed. In terms of key management, a key updating mechanism solves the problem of security risks caused by increase of the number of times of use of the key, and security threats caused by key leakage are prevented. The key backup mechanism ensures the recoverability of the key, and avoids the situation that the system cannot operate normally due to the loss or damage of the key. According to the access control system, transaction records are stored and managed through the block chain technology, the problems of data integrity, traceability and high efficiency in the management process of the access control system are solved, automatic management is achieved, and the safety and stability of the whole access control system are improved.

The invention relates to the technical field of biological feature image recognition, and discloses an image fusion recognition method and device based on an ultra-light network, a medium and equipment, and the method comprises the steps: carrying out the feature extraction of an input multi-modal image through employing an improved Co3Net network module, and obtaining a multi-scale feature; carrying out feature extraction on the input multi-scale features by adopting an ultra-light network module to obtain global features; a self-attention mechanism module is adopted to obtain a self-attention map according to the input global features; performing forward propagation on the self-attention map by adopting a forward propagation unit to obtain final forward propagation output; and adopting a classifier to obtain a multi-modal image classification label according to the final forward propagation output. By applying the method, the calculation complexity and parameter quantity of the palm print and palm vein recognition method can be reduced, and the problem that the method is difficult to operate efficiently on embedded equipment and mobile terminals with limited resources is solved.

The invention discloses a method and system for testing human body static electricity through identity recognition based on palm veins, and relates to the technical field of image recognized.The system comprises an image acquisition module, a feature fusion module, an identity recognition module, a static electricity testing module and a state display module.The microcirculation pulsation is detected through a time-space domain light intensity distribution model, and the human body static electricity is detected through a time-space domain light intensity distribution model; the light intensity change rate is quantified, so that a living body detection mechanism is established, accurate recognition is performed through a multispectral fusion technology, palm vein images are acquired by adopting multi-wavelength infrared light, the defect of single-band imaging is overcome, the anti-interference capability is improved, and the feature extraction precision is improved; according to the method, the light intensity parameter HSV and the color parameter RGB of the multi-source image are integrated, the fused image is constructed, through palm vein image feature recognition and matching, the identity of a tester is compared and judged, the vein texture recognition degree is enhanced, the recognition deviation is reduced, the safety level is high, the test time is short, and more reliable and accurate data analysis is provided for the enterprise big data era.

The invention discloses a highly convenient and safe palm lock, which comprises a lock body, a palm print acquisition module, a palm vein acquisition module, an iris recognition module, a control unit and a mechanical execution unit, and is characterized in that the palm print acquisition module is used for acquiring palm surface texture features and comprises an optical imaging unit and an infrared light supplement lamp; the palm vein acquisition module is used for acquiring vein blood vessel distribution characteristics in a palm and comprises a near-infrared light source and an infrared sensor; the iris recognition module is used for obtaining human eye iris texture features. Therefore, single-feature quick unlocking (convenience) and multi-feature combined verification (high safety) are supported, a user can dynamically configure a verification mode through a mobile phone APP to adapt to different scene requirements (such as household daily palmprint and office palmprint + iris), the three biological features are independently collected, the forging difficulty is high, the combined verification safety is high, and the verification efficiency is high. The palm fitting area is designed to be arc-shaped and aligned with the camera, and the identification time is less than or equal to 2 seconds.

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.

The invention discloses a non-contact palm vein multi-mode identification system based on deep learning. The system comprises a multi-mode image acquisition and processing terminal, a mode matching and identification decision terminal, a safety protection and anti-counterfeiting terminal and an iterative optimization terminal. The multi-modal image acquisition and processing terminal is used for acquiring palm print and palm vein images, performing dynamic calibration, image quality enhancement and preprocessing, and outputting multi-modal images; the mode matching and identification decision terminal is used for carrying out feature extraction, multi-modal feature fusion, mode matching and identification decision and outputting a final matching result; the safety protection and anti-counterfeiting terminal is used for carrying out living body detection, anti-counterfeiting monitoring and data encryption; and the iterative optimization terminal is used for realizing model lightweight, knowledge distillation, end-to-end optimization and continuous learning. According to the invention, through deformation invariant feature extraction and cross-modal attention fusion, the recognition accuracy and environmental adaptability in a complex state are improved.

The invention provides a palm vein high-security identity authentication system based on spectral analysis and deep learning, and relates to the technical field of biological recognition, the system comprises a hardware layer, a data processing layer, an algorithm layer and an application layer, through an antagonistic living body detection module in the algorithm layer, in combination with physical modeling and a GAN (Generative Adversarial Network), the high-security identity authentication of a complex imitation is realized. The method comprises the following steps: carrying out effective identification of a high-biomimetic material, carrying out physical modeling to analyze the absorption characteristics of palm veins in a hyperspectral range, such as the difference between oxyhemoglobin and oxyhemoglobin and periodic spectrum micro-interference caused by heart rate, and providing living body evidence based on physiological dynamics; meanwhile, a high-simulation template sample generated by the GAN is used for training a discriminator, the insight ability of the system to a template means is further enhanced, and compared with single traditional texture or static signal detection, the system combines physical characteristics with deep learning, and the confidence coefficient of in-vivo detection reaches up to 99.99%.

The invention provides a palm vein dynamic capture and deep learning identity recognition terminal, which relates to the technical field of biological feature recognition, and comprises a dynamic capture module, a deep learning identity recognition module and an implementation processing and feedback system, the dynamic capture module collects multiple frames of palm vein images and combines a deep convolutional neural network and recurrent neural network hybrid model of the deep learning identity recognition module, abundant space and time sequence features can be extracted, a high-distinction-degree comprehensive feature vector is generated, meanwhile, vein features under the complex background are adaptively learned, and the recognition accuracy is improved. Recognition precision and robustness are remarkably improved, interference such as light changes and skin states is adapted, a palm is supported to move freely within a certain range, the palm does not need to be kept static deliberately, the time of the whole process from dynamic capture to identity recognition is shortened to be within one second through a high-performance embedded processor and an optimization algorithm in combination with a real-time processing and feedback system, and the recognition efficiency is improved. Therefore, the method is suitable for a rapid identity authentication scene.

The invention relates to the technical field of image fusion and classification, and discloses a multi-modal image fusion recognition method and device, a medium and equipment. The method comprises the following steps: acquiring different types of multi-modal images; performing shallow feature extraction on the multi-modal image by using a convolutional layer, and performing feature fusion to obtain shallow fusion features; performing global feature extraction on the shallow fusion features to obtain global features; performing feature fusion on the shallow fusion features and the global features to obtain deep fusion features; performing local feature extraction on the deep fusion features to obtain local features; and performing full connection processing on the local features, and identifying to obtain a category label of the multi-modal image. By applying the method, fusion identification of the palm print and palm vein multi-mode images can be realized, and the identification accuracy and the equal error rate on a public data set and an incomplete data set are improved.

The invention discloses a palm vein recognition method based on a domain adaptation strategy, and relates to the technical field of biological information recognition, identity authentication and palm recognition, and the method comprises the steps: 1, constructing a data set which comprises a source data set and a target data set, and employing all data in the source data set and part of data in the target data set as an initial training set, using other data in the target data set as an initial test set, then performing ROI extraction, segmenting the initial training set into a formal training set, and segmenting the initial test set into a formal test set; 2, designing an adversarial domain adaptation network; 3, pre-training is carried out on the source data set, so that the classification module can reach preset classification performance on the source data set; 4, adversarial training is carried out on the formal training set, so that the palm feature extraction module learns domain-invariant features, and when the training reaches a preset iteration frequency or a model threshold value, the training is ended; and 5, testing by using the formal test set.

The invention relates to the technical field of artificial intelligence, and discloses a palm vein recognition method and device based on human anatomy, equipment and a medium, and the method comprises the steps: obtaining a palm vein image sequence of a user; carrying out anatomical key point positioning processing on the palm vein image sequence to obtain anatomical key point coordinates of the palm vein image sequence; according to the anatomical key point coordinates, carrying out geometric correction processing on an ROI region of the palm vein image sequence to obtain a standardized ROI region sequence; performing multi-modal feature extraction processing on the standardized ROI region sequence to obtain vein texture features and hemodynamic features; and performing cross-modal fusion processing on the vein texture features and the hemodynamic features to obtain palm vein fusion features. According to the invention, the recognition rate and safety of palm vein recognition can be improved.

The present invention provides a palm vein edge refinement detection method that incorporates cross-self-attention. The method comprises: obtaining a palm vein image to be processed; inputting the image into a trained palm vein edge refinement detection network to obtain edge information. The palm vein edge refinement detection network comprises a feature extraction unit for extracting local details and global structure, a feature fusion unit for fusing features of different scales in space and channels, and a feature refinement unit for segmenting the fused features. The method first extracts local details and global features using the feature extraction unit, then uses the feature fusion unit to aggregate features of different scales in space and channels, and finally uses the feature refinement unit to specifically refine uncertain points in the initial prediction results, thereby achieving accurate segmentation of palm vein edges.

1. Name of the Design Product: Palm Vein Recognition Device. 2. Use of the Design Product: Used for collecting palm vein images and realizing identity recognition and authentication. 3. Design Key Points of the Design Product: Lies in the shape. 4. Picture or Photograph that Best Illustrates the Design Key Points: Perspective View.

The present application belongs to the technical field of palm vein recognition, and particularly relates to a palm vein recognition data enhancement method and system based on adversarial learning, which utilizes a conditional deep convolutional generative adversarial network composed of a generator and a discriminator, and synchronously trains the generator and the discriminator; step 2 selects a palm vein classifier and the trained generator to form an adversarial network, step 3 performs multiple batches of adversarial training on the palm vein classifier based on the adversarial network, generates adversarial samples for increasing the loss of the classifier and training samples based on real palm vein recognition data to form an augmented data set in each batch of training, trains the classifier, and updates the parameters of the classifier; and updates the noise vector set required for the next batch of adversarial training. The present application reduces the requirements for computing and storage resources in data enhancement, and provides more high-quality training samples for palm vein recognition model training.

1. Name of the product in this design: Two-in-one time attendance machine (horizontal 4.3-inch). 2. Purpose of this design: This design product uses facial or palm vein recognition for identity verification to achieve attendance management. 3. The key design feature of this product is its shape. 4. The image or photograph that best illustrates the design's key points: a 3D model.

The utility model discloses a non-contact palm vein recognition intelligent security and protection management terminal, which comprises a security and protection module and at least two identity verification modules including a palm vein verification module. The non-contact palm vein recognition intelligent security management terminal further comprises a hierarchical authorization module which is connected with the security module and the palm vein verification module, and the hierarchical authorization module is used for granting a set permission to a security application module when verification of the palm vein verification module is passed. The palm vein verification module is a non-contact palm vein verification module; according to the utility model, the security of the security management terminal can be improved, and the accuracy and efficiency of identity verification of the security management terminal can be improved at the same time.

The utility model discloses a multi-mode palm vein recognition terminal machine which comprises a multi-mode palm vein recognition terminal machine body, the outer wall of the multi-mode palm vein recognition terminal machine body is fixedly connected with a shell, the top ends and the bottom ends of the two sides of the multi-mode palm vein recognition terminal machine body are respectively provided with a square plate, and the square plates are fixedly connected with the inner wall of the shell. The two sides of the multi-mode palm vein recognition terminal machine body are each provided with two guide rods, the guide rods are fixedly connected with a square plate, the two guide rods located on the same side are sleeved with the same sliding plate, the sliding plates are slidably connected with the guide rods, and one side of each sliding plate is fixedly connected with a fixing base. According to the utility model, the multi-mode palm vein recognition terminal machine body can be effectively protected, the multi-mode palm vein recognition terminal machine body can be conveniently cleaned, dust is prevented from blocking a sensor, the quality of captured images is ensured to be clear, a user can clearly see displayed content, and the use experience of the user is ensured.

The invention relates to the technical field of palm vein recognition, in particular to an efficient palm vein representation attack detection method and system based on a lightweight neural network. The method comprises the following steps: acquiring an image to be identified; inputting a to-be-recognized image into the Xception entry stream, and performing preliminary feature extraction on the to-be-recognized image to obtain an initial feature; inputting the initial features into Block modules of a star network, and further mining high-order nonlinear features in the image by each Block module through convolution and star operation; and performing classification identification on the high-order nonlinear features to obtain classification result data. Real and forged palm vein images are distinguished by capturing vein texture features in the images, a single-channel near-infrared palm vein image is input, and a binary result of true and false classification is output.

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 embodiment of the invention discloses a palm vein information acquisition system, method and device, and the method comprises the steps: collecting palm vein image data through an image collector, obtaining the biological parameter information of the palm vein image data through an image recognition module, and determining whether the palm vein image data is abnormal or not according to the biological parameter information; and when the palm vein image data is normal, identifying the palm vein image data to obtain a palm region, performing alignment processing on the palm region, extracting palm vein vector feature information of the palm region, sending the palm vein vector feature information to the server, pre-processing the received palm vein vector feature information by the server, and matching a target search result, according to the embodiment of the invention, the collected palm vein image data is processed, so that the output of the palm vein image can be enhanced, the subsequent detection of the palm vein image data can be facilitated, the judgment type of the palm vein state can be expanded, the requirement for placing the palm of an identifier during passing is reduced, and the passing efficiency is improved.

The utility model relates to the technical field of cash registers, and discloses a small-size multifunctional cash register which comprises a main body, a front screen arranged in the main body, a rear screen arranged in the main body, a palm vein camera arranged in the main body, and a code scanning camera arranged in the main body. And a card swiping sensing module is arranged in the main body. According to the small-size multifunctional cash register, the position of the front screen is adjusted, the camera and the sensing module are arranged on one side of the front screen, the effect that the camera and the sensing module can be contained without enlarging the size of the cash register is achieved, a clamping groove is formed in the main body, components are clamped in the main body, and the clamping groove is formed in the main body; the interior of the main body is more compact and higher in stability, heat dissipation can be achieved by using small heat dissipation fins by using the processor with smaller heat productivity after upgrading, and the problem that the size of the cash register is increased due to the fact that the cash register uses the processor with higher performance and is provided with a plurality of cameras and sensing modules is solved.