40 results about "Vein recognition" patented technology

The invention belongs to the technical field of vein recognition, and particularly relates to a metal vein recognition method and system based on a rock core image, and the method comprises the steps: carrying out the gray conversion, enhancement and filtering processing of a collected RGB rock core image, and building a gray reference image; analyzing the gray similarity of a pixel point space neighborhood, and calculating a local texture width index to measure the physical width of the texture; gaussian mapping is carried out based on the index, and the matching weight of the multi-scale candidate window is adaptively acquired; in combination with the matching degree and gradient information, a vein index is calculated through multi-scale texture fusion and a nonlinear fracture suppression model, so that a real vein and a natural fracture are distinguished; and obtaining a binary vein distribution map by using an Otsu method and morphological operation. According to the method, the problems of complex background interference, inaccurate fixed window feature extraction and fracture misrecognition are reduced, and the vein recognition precision is improved.

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.

A blood vessel image segmentation method and device, electronic equipment and storage medium are disclosed. The method comprises: acquiring an initial blood vessel image, determining a coronary skeleton image of the initial blood vessel image; determining each skeleton point on the skeleton line in the coronary skeleton image, and determining at least one partition skeleton point in each skeleton point based on the degree of each skeleton point; determining the partition skeleton line segment corresponding to each partition skeleton point, and performing vein identification on each partition skeleton line segment to determine the vein branch line segment in the coronary skeleton image; and determining the coronary segmentation image of the initial blood vessel image based on the initial blood vessel image and the vein branch line segment. The technical solution disclosed in the present application solves the problem of low accuracy of coronary segmentation of blood vessels in the prior art, and improves the accuracy of coronary segmentation.

This utility model relates to the field of intelligent document safes, specifically an intelligent document safe comprising a main body, a security mechanism, an auxiliary mechanism, and a power supply mechanism. The security mechanism is located outside the main body, the auxiliary mechanism is located inside, and the power supply mechanism is located inside the main body. This utility model provides multiple protection measures for the safe through the arrangement of the 3D structured light facial recognition module, the display screen, and the vein recognition module in the security module, as well as the anti-drill mechanical lock cylinder. Furthermore, the cabinet structure is made of three layers of composite board composed of different materials, which reduces weight while significantly improving fire resistance and anti-theft performance. At the same time, the power supply mechanism supplies power to the security mechanism. The power supply mechanism is equipped with a rechargeable lithium battery that can last for up to two years and is also equipped with a hand-cranked generator for backup power in emergencies. In addition, a dehumidifying box is added to prevent prolonged moisture interference to electronic components, thereby extending the service life of the electronic components.

The method comprises the steps that when it is detected that the palm of a user is placed on a door handle, a bottom palm vein recognition module is triggered to recognize palm center veins of the palm, and when the palm center veins pass verification, the bottom palm vein recognition module is triggered to recognize the palm center veins of the palm; a top palm vein recognition module is triggered to recognize hand back veins of a palm, and after verification of the hand back veins is passed, the intelligent door lock is controlled to be unlocked; or when it is detected that the palm of the user is placed on the door handle, the top palm vein recognition module is triggered to recognize the hand back vein of the palm, after the hand back vein verification is passed, the bottom palm vein recognition module is triggered to recognize the palm center vein of the palm, and after the palm center vein verification is passed, the intelligent door lock is controlled to be unlocked. According to the invention, through a palm double-sided vein recognition mechanism, unlocking is carried out only when the comparison of double characteristics is passed, so that the recognition safety of the intelligent door lock is improved.

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.

The application discloses a palm vein recognition method and device, equipment and storage medium, the method comprises: through the camera shoots palm image, and through the palm detection model of pre-training from palm image identifies first palm area;In the case where the target brightness value of the first palm area does not satisfy the preset brightness range, the exposure of the camera is adjusted according to the target brightness value, and the next palm image is shot by the camera;In the case where the target brightness value of the first palm area satisfies the preset brightness range, the second palm area is identified from the palm image;Palm vein features are extracted from the second palm area to determine the corresponding identity information according to the palm vein features. Through the above technical means, the palm area in the palm image is detected, the camera exposure is adjusted according to the brightness value of the palm area, so that the palm image with appropriate brightness is quickly collected for palm vein recognition, the recognition efficiency is improved, and the problem that the palm vein recognition in the prior art takes a long time is solved.

The present invention relates to a miniaturized vein recognition module and a B-pillar trim panel integrated with same. The miniaturized vein recognition module comprises a camera module, a controller module and a micro switch module. The controller module comprises a PCBA, an MCU component, an SOC component and an RGB lamp being integrated onto the PCBA. The micro switch module is pressed by a hand to wake up and power on the vein recognition module. The camera module recognizes and collects palm vein feature information and transmits same to the controller module. The SOC component inside the controller module executes vein extraction, enhancement and feature comparison and the MCU component transmits a vein recognition result to an in-vehicle infotainment system, so that an in-vehicle infotainment center console gives feedback to lock and unlock vehicle doors. The present invention eliminates an original module housing structure, so that a required trim panel interior space size is relatively small, thereby better satisfying requirements for miniaturized B-pillar trim panels of framed and frameless vehicle doors.

The invention relates to a physical method for correcting LSC based on screen printing, which belongs to the technical field of image processing, and comprises the following steps: constructing a relative illumination curve of a lens in vein recognition equipment; calculating a light intensity adjustment coefficient of each near-infrared lamp bead in the vein recognition equipment according to the relative illumination curve; screen printing is designed according to the light intensity adjustment coefficient; and covering a near-infrared optical filter above a near-infrared lamp bead of the vein recognition equipment with the silk screen. According to the method, the vein recognition speed is increased while the production efficiency of vein equipment is improved.

The application discloses a method and system for extracting vein features. The method comprises the following steps: acquiring a vein image; pre-processing the image to obtain a gamma enhanced image; setting a scale factor and a sliding window; extracting principal curvature information of the gamma enhanced image; taking the minimum value of the principal curvature information of the gamma enhanced image, and obtaining a Hessian matrix enhanced image according to a multi-scale response; performing local histogram equalization to obtain a local histogram equalization enhanced image; and binarizing and performing morphological processing on the local histogram equalization enhanced image to obtain a final result. The application can effectively suppress background noise interference, reduce the influence of environmental factors on vein recognition, thereby improving the distinguishability and recognition accuracy of the vein image, and enhancing the robustness and generalization ability of the model.

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 application relates to the technical field of biometric image recognition, and discloses an image fusion recognition method, device, medium and equipment based on an ultralight network, the method comprising the following steps: adopting an improved Co3Net network module to perform feature extraction on inputted multi-modal images to obtain multi-scale features; adopting an ultralight network module to perform feature extraction on the inputted multi-scale features to obtain global features; adopting a self-attention mechanism module to draw a self-attention graph according to the inputted global features; adopting a forward propagation unit to perform forward propagation on the self-attention graph 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. The application can reduce the calculation complexity and parameter quantity of a palm print and palm vein recognition method, and solves the problem that the method is difficult to efficiently run on resource-limited embedded devices and mobile terminals.

The utility model discloses a finger vein recognition mechanism which is used for reducing the influence of dust in the environment on a finger vein recognition area and improving the recognition rate. The device comprises a finger vein assembly, a track box and a sliding track structure, a containing space is formed in the track box, the finger vein assembly partially penetrates through the track box and is located in the containing space, and the side wall of the finger vein assembly is movably connected with the inner wall of the containing space through the track sliding track structure; the finger vein assembly comprises a working position and a storage position, and at the storage position, a recognition module on the finger vein assembly is located in the containing area; and at the working position, the finger vein assembly is controlled to slide along the sliding track structure, so that the upper end of the finger vein assembly slides out of the accommodating area.

The utility model provides a charging gun for image acquisition. The charging gun comprises a charging port (1), a grip base (2), a transparent grip (3), a cable (4) and a palm print and vein recognition circuit, wherein the palmprint and vein recognition circuit comprises a reverse telescopic camera (7), a forward telescopic camera (8), a recognition mainboard (9) and an auxiliary camera (10); the grip base (2) is connected with the charging gun main body and is fixed with the charging gun main body; the transparent grip (3) is positioned in the middle of the grip base (2) and is cylindrical and transparent; an identification mainboard is arranged in the transparent grip (3); the reverse telescopic camera (7) and the forward telescopic camera (8) are positioned on the front side and the back side of the identification mainboard (9); the auxiliary camera (10) is located behind the grip base (2) and is in a protruding shape. The auxiliary camera (10) is in a look-up shape. Palm print and vein images of a charging user can be rapidly and accurately collected, and the charging efficiency is improved.

The embodiment of the invention provides a finger vein recognition technology (FIVRT) based on deep learning, and relates to a finger vein recognition method based on deep learning. The finger vein recognition technology is one of biological feature recognition technologies, has the characteristics of living body recognition, non-replicable in-vivo features, uniqueness, stability, non-cracking and the like, and has a higher safety coefficient than fingerprint recognition and face recognition. According to the embodiment of the invention, the finger vein feature values are extracted by using the FingerCavaNet network model and mapped into the feature vectors in the Euclidean space, the similarity between the two pieces of finger vein data is measured through the Euclidean distance between the two feature vectors, and the smaller the Euclidean distance is, the higher the similarity is. Therefore, personal identity authentication and identity confirmation are realized. The shape of the finger vein has uniqueness and stability, that is, the finger vein images of each person are different, the vein images of different fingers of the same person are also different, and the vein shape of a healthy adult does not change any more, so that a basis is provided for the finger vein to be used for identity recognition.

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 application discloses an adaptive vein template registration method and device, and belongs to the technical field of biometric recognition. The adaptive vein template registration method comprises the following steps: performing feature extraction and image quality analysis on a plurality of acquired initial sample vein images, and acquiring a first sample feature and a first quality score respectively; performing deduplication processing on the plurality of initial sample vein images based on the first sample feature and the first quality score, and acquiring a plurality of first sample vein images; and acquiring a target template vector from the plurality of first sample vein images based on a first feature similarity between a target sample vein image and remaining sample vein images other than the target sample vein image and a first threshold. The adaptive vein template registration method can select the most representative vein samples at different angles as templates, reduces the number of templates, and can reduce the consumption of storage space while improving the vein recognition performance.

The application discloses a kind of finger vein identification method, device, computer readable storage medium and equipment, belong to the field of biometric identification.It includes: obtaining finger vein image;Calculate the gradient information of finger vein image, according to gradient information, find the finger boundary using greedy strategy;Detect finger joint on finger vein image, and extract the effective area of finger vein according to the finger joint and finger boundary;Through Gabor filter, the effective area is extracted, and the finger vein feature is obtained;Set sliding window on the finger vein image, and the finger vein feature of the finger vein image in sliding window is compared with the corresponding position of the finger vein feature template Similarity, find the finger vein image in the highest similarity sliding window as the maximum matching area;The similarity of maximum matching area and the corresponding position of finger vein feature template is used as matching score.The application can realize stable and efficient finger vein identification for different devices and different collection environments.

The application discloses an ultrasonic and infrared combined palm print and palm vein identification method, equipment and device, relates to the field of biological information identification and identity authentication, and comprises the following steps: step 1, collecting original images, including a palm vein image and an ultrasonic palm print image; step 2, performing ROI extraction, identifying the region of palm biological feature information contained in the original image, and obtaining two ROIs, namely the ROI of the palm vein image and the ROI of the ultrasonic palm print image; step 3, inputting the ROI of the palm vein image into a feature encoder 1 and the ROI of the ultrasonic palm print image into a feature encoder 2, and respectively extracting palm vein features and palm print features; step 4, in the process of feature extraction, synchronously performing bidirectional feature fusion, and finally obtaining multi-scale features; and step 5, inputting the multi-scale features into a classifier for classification identification, and outputting a classification result.

A finger vein recognition device based on screen printing correction LSC relates to the field of biological recognition and comprises a shell, a near-infrared lamp band composed of near-infrared lamp beads, a near-infrared optical filter, screen printing and a camera device. The shell is provided with a vein collection window, the near-infrared lamp strip is installed on the side edge of the vein collection window, and near-infrared light emitted by the near-infrared lamp strip can enter the vein collection window after transmitting a target object; the near-infrared light filter covers the upper side of the near-infrared light strip; the silk screen is arranged on one side, close to the vein acquisition window, of the near-infrared optical filter; the camera device is installed in the shell and used for receiving light rays entering the vein collection window for induction imaging. According to the equipment, LSC correction is realized through a physical scheme, an image processing algorithm does not need to be adopted, LSC correction on each module is avoided, the production efficiency is improved, the optimization time of the image is not increased, and the finger vein recognition speed is further improved.

The application discloses a palm outline detection method and device, a storage medium and equipment, and belongs to the palm vein recognition field.The method comprises the following steps: adaptively setting a segmentation threshold according to an input image; performing binary segmentation on the input image by using the adaptively set segmentation threshold to obtain a foreground region and a background region; and finding a palm boundary based on the palm region to obtain a palm outline.In the binary segmentation process, the segmentation threshold is adaptively set according to the input image, the result after the input image is segmented by using the adaptively set segmentation threshold is more accurate, and the accuracy of palm outline detection is improved.

1. Name of the product in this design: Smart door lock with graphical user interface for door lock operation. 2. Purpose of this design: This design is a smart door lock that can be unlocked using methods such as palm vein recognition, fingerprint recognition, and password. 3. The key design features of this product are its shape and the content of its graphical user interface. 4. The image or photograph that best illustrates the design's key points: a 3D model. 5. Purpose of the graphical user interface: The rectangle at the top of the main view is the display screen, and the content other than the middle A is the interface content. Users can activate palm vein recognition and unlock the door by approaching the palm vein icon on the interface, or enter a password by clicking the numbers on the interface to unlock, or enter numbers and then click the icon below the number 9 to confirm and unlock the door, or click the doorbell icon at the bottom of the interface to ring the doorbell. 6. Other situations requiring explanation: In the main view, A is the fingerprint reader.

This application provides an electric two-wheeled vehicle, relating to the field of electric two-wheeled vehicle technology. The electric two-wheeled vehicle includes: a steering system comprising two throttles and a dashboard; a front cover, at least partially located below the throttles; a finger vein recognition module disposed on the throttles, the front cover, or the dashboard, the finger vein recognition module for collecting finger vein image information of the user, the finger vein recognition module including a housing and a recognition surface disposed on the housing; and a control system connected to the finger vein recognition module, the control system for controlling vehicle unlocking based on the verification result of the finger vein recognition module; the spatial posture of the recognition surface is configured such that when the user prepares to operate the electric two-wheeled vehicle, the user's finger is adapted to move in a direction approximately perpendicular to the recognition surface to contact the recognition surface. This electric two-wheeled vehicle can achieve fast unlocking without relying on external devices such as keys, NFC cards, or electronic devices, making unlocking more convenient for users and improving the user experience.

This application relates to the field of biometric recognition and image processing technology, and discloses a method, model, device, and medium for finger vein recognition based on a lightweight attention model with few samples. The method includes: acquiring raw finger vein images and extracting regions of interest (ROIs); preprocessing the ROI images; performing data augmentation on the training set images; constructing an LA-VGG network based on a VGG-19 network, introducing CA attention, PReLU, and cross-layer fusion to enhance subtle textures; introducing a loss function with additive angular margins during the training phase; training the LA-VGG network to obtain a finger vein recognition model; inputting the image to be recognized into the model, and outputting the identity recognition result. This invention can effectively alleviate the overfitting problem under small sample conditions, reduce the number of model parameters and computational complexity, improve the extraction capability of key finger vein texture features, and is suitable for deployment and application in resource-constrained devices and complex environments.

This application discloses a palm vein recognition method, apparatus, device, and storage medium. The method includes: inputting a first palm vein image to be recognized into a pre-trained global feature extraction model to obtain a global feature image output by the global feature extraction model; performing key point detection on the first palm vein image, and extracting first image blocks corresponding to each key point from the first palm vein image based on the key points in the first palm vein image; extracting first local feature vectors of each first image block through a pre-trained local feature extraction model; matching multiple candidate palm vein images from multiple second palm vein images through the global feature image, determining the target palm vein image from the multiple candidate palm vein images through each first local feature vector, and determining the identity information of the target palm vein image as the identity information of the first palm vein image.

The utility model relates to the technical field of palm vein recognition, solves the technical problem that the accuracy of face recognition and palm vein recognition cannot be improved under dark conditions in the prior art, and particularly relates to a face recognition and palm vein recognition system, which comprises a micro-processing module, the palm vein recognition system further comprises a first image module, a second image module, a voice module, an audio amplification module and a voltage stabilization module, and the first image module comprises an external power source, an image analysis chip, current limiting resistors R1, R2 and R3 and a light sensation triode Q1. According to the technical scheme, the luminous intensity of the LED can be changed according to the light intensity in the environment, and then the face and palm vein areas are illuminated, so that the accuracy of face recognition and palm vein recognition can be greatly improved, the use experience of a user is improved, and meanwhile, the safety of the face recognition and palm vein recognition system can also be improved.

The application belongs to the technical field of biometric recognition, and specifically discloses a K-nearest neighbor graph iteration vein recognition method based on deep learning, which comprises the following steps: obtaining a feature vector of a to-be-tested vein image and a feature vector set of a vein image training set, a distance between the feature vector and each feature vector in the feature vector set, and selecting k feature vectors with the smallest distance from the feature vector set; inputting the k+1 feature vectors and corresponding label information into a graph iteration model to iteratively learn the correlation between the feature vectors and simultaneously predict the label information of the to-be-tested vein image, so as to realize the final prediction of the classification recognition of the to-be-tested vein image. The application also discloses a vein recognition system based on the method. The application solves the technical problem that the prior art does not fully utilize the distance information and correlation information between the feature vectors of corresponding samples, so that the prediction label accuracy is not high.

The invention relates to the technical field of intelligent ultrasonic examination, and discloses a risk assessment method and system based on a vascular ultrasonic image, a terminal and a storage medium, and the method comprises the steps: obtaining ultrasonic echo data of a wearable ultrasonic patch, carrying out the reconstruction processing of the ultrasonic echo data, and obtaining the vascular ultrasonic image; acquiring clinical risk factors of a patient, analyzing the vascular ultrasound image according to a vein recognition and compressibility analysis algorithm and a texture and blood flow feature extraction algorithm to obtain vein image features, and inputting the vein image features and the clinical risk factors into the trained risk assessment model for assessment to obtain a venous thrombosis risk score; and obtaining a timestamp and historical data, determining a risk level according to the timestamp, the historical data and the venous thrombosis risk score, and sending alarm information to medical personnel. The venous thrombosis risk is dynamically assessed by constructing the risk assessment model, and accurate monitoring and graded early warning of the venous thrombosis risk of the patient are achieved.

1. Name of the product in this design: Multifunctional Palm Vein Recognition Device. 2. Application of this design: It is used for palm scanning and palm vein recognition, and can be used in payment applications and various access control and attendance systems. 3. The key design feature of this product is its shape. 4. The image or photograph that best illustrates the design's key features: the front view.

The application belongs to the technical field of biological feature recognition, and discloses a finger vein recognition method based on an improved automatic coding network. The method is based on the improved automatic coding network, can learn the structure and features from unmarked data in an unsupervised manner, and improves the recognition accuracy. An error correcting code (ECC) suitable for real value features is used to protect the template, so that the security can be improved, the loss of detail information can be avoided, and the sensitivity and accuracy of the recognition system are improved.