75 results about "Vein recognition" patented technology

The invention belongs to the technical field of medical informatization, and provides an anesthesia medication management system with biological recognition, comprising: a biological recognition module verifies the identities of medical staff and patients through a vein recognition technology; the multi-source data acquisition module acquires vital sign data and equipment parameters of a patient in real time to obtain multi-source data; the intelligent drug management module authorizes to store and take drugs according to the biological recognition result and generates an electronic anesthesia prescription; the processing decision module receives the multi-source data and generates a medicine adjusting instruction through a preset rule and an algorithm in combination with an electronic anesthesia prescription; the execution control module carries out secondary confirmation on the medicine adjusting instruction through biological recognition and then sends the medicine adjusting instruction to anesthetic infusion equipment to be executed; according to the method, through the electroencephalogram double-frequency index, the entropy index and the hemodynamic parameters, in combination with the anesthesia depth evaluation result and the personalized drug metabolism and effect model, the medication scheme is dynamically adjusted, the optimal infusion rate is generated, the anesthesia depth control is more accurate, and the fluctuation range is narrowed.

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 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 invention provides a limb thrombus monitoring device and method based on arteriovenous recognition, and the device comprises a monitoring management middle platform, a multi-modal data collection module, a vein recognition module, a feature extraction module, and a risk assessment module. The monitoring management middle platform is connected with the multi-modal data acquisition module, the vein recognition module, the feature extraction module and the risk assessment module, and manages each unit; the multi-modal data acquisition module is used for acquiring image data of limb parts of a patient; and the vein recognition module is used for recognizing and positioning the limb vein position of the patient based on the near-infrared imaging data to obtain vein position information. The accuracy of thrombus monitoring, evaluation and judgment can be improved, and the problem that the thrombus monitoring process mainly depends on clinical experience of medical staff for judgment is avoided. Therefore, the thrombus monitoring and judging efficiency and accuracy are 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 vein feature extraction method and system. The method comprises the following steps: acquiring a vein image; preprocessing 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 the multi-scale response; carrying out local histogram equalization to obtain a local histogram equalization enhanced image; and carrying out binarization and morphological processing on the local histogram equalization enhanced image to obtain a final result. According to the method, background noise interference can be effectively suppressed, and the influence of environmental factors on vein recognition is reduced, so that the distinguishability and recognition accuracy of the vein image are improved, and the robustness and generalization ability of the model are enhanced.

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 invention discloses a method for recognizing palm prints and palm veins in a missing mode based on multi-level knowledge distillation, and provides three innovation points aiming at the problem that semantic information of different levels of a teacher network cannot be fully mined by a traditional distillation method: (1) knowledge distillation is carried out on three progressive levels of the teacher network, and in addition, the knowledge distillation is carried out on the three progressive levels of the teacher network; logic output is also subjected to fine-grained alignment, and it is ensured that the reasoning network fully learns overall semantic knowledge of the teacher network. (2) proposing a cross-modal feature distribution correlation distillation mechanism, and encouraging the reasoning network to learn representation correlation knowledge among modals instead of focusing on transmission of knowledge in a single modal; and (3) providing structural knowledge of distribution angles and distances of feature vectors of different samples in a high-dimensional space based on structural knowledge distillation among samples guided by classification boundaries, and meanwhile, enabling the inference network to pay more attention to the samples with classification uncertainty through a classification boundary guiding mechanism so as to refine the extracted structural knowledge.

The invention provides an access control method and system based on artificial intelligence and Internet of Things, and is applied to an access control system, the access control system comprises a restricted access area door, and the restricted access area door is provided with a restricted acquisition camera; comprising the following steps: collecting a plurality of frames of walking images of a passing requesting person through the collection limiting camera; obtaining multiple frames of human body postures of the passing requesting person based on the multiple frames of walking images; the multiple frames of human body postures are sent to a human body walking dynamic analysis model, and the walking dynamic state of the passing requesting person is obtained; and if the walking dynamic state of the passing requesting person is a passing permission dynamic state, unlocking the access restriction area door, and performing biological feature recognition on the passing requesting person in the process that the passing requesting person moves to the access restriction area door. The problems that the door opening time is long and the efficiency is low due to the fact that a person needs to stand in front of a door to wait for recognition and unlocking in the existing biological recognition technology of fingerprint, iris, face recognition and vein recognition can be 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 discloses an intravenous injection processing method based on image recognition and a related device. The method comprises the steps that a first size parameter of a needle of a to-be-injected injection tool is determined; acquiring a first image of a target part of the target object through a vein recognition module; performing vein line extraction on the first image to obtain a vein line graph; dividing the vein line graph into a plurality of sections to obtain a plurality of sections of vein line areas; determining the average width of each vein line area in the plurality of sections of vein line areas to obtain a plurality of average widths; determining the position of each vein line area in the plurality of sections of vein line areas to obtain a plurality of positions; evaluating each vein line region in the plurality of sections of vein line regions according to the plurality of average widths and the plurality of positions to obtain a plurality of score values; and selecting a maximum value in the plurality of score values, and determining a target vein line area corresponding to the maximum value. By adopting the embodiment of the invention, medical personnel can be quickly helped to find the intravenous injection position.

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.

Facial vein and palm vein integrated equipment relates to the technical field of vein recognition equipment, and comprises a frame body, a camera, a recognition module and a control module, the camera comprises a facial vein acquisition camera and a palm vein acquisition camera, the facial vein acquisition camera is fixed on the front surface of the frame body, and the palm vein acquisition camera is fixed on the side surface of the frame body; the recognition module is mounted in the frame body and is in communication connection with the facial vein acquisition camera and the palm vein acquisition camera; the control module is installed in the frame body and is in communication connection with the identification module. The equipment integrates facial vein identity recognition and palm vein identity recognition, and is higher in flexibility and wider in use scene.

The utility model relates to the technical field of door locks, in particular to a vein recognition intelligent door lock front plate which comprises a door lock front plate body, the door lock front plate body comprises a base and a panel, the upper end of the panel is provided with a connecting block connected with the base, the rear side of the lower end of the panel is provided with a connecting column connected with the base, and the connecting column is used for installing a lock cylinder. A gap is reserved between the panel and the base, a finger vein module is arranged on the rear side of the upper end of the panel, an air outlet corresponding to the finger vein module is formed in the front side of the upper end of the base, an air inlet is formed in the side wall of the lower end of the base, a miniature air blower and an air duct are arranged in the base, the upper end of the air duct is communicated with the air outlet, and the lower end of the air duct is communicated with the miniature air blower. The micro air blower is communicated with the air inlet, a dehumidification switch is arranged on the front side wall of the panel, and a controller electrically connected with the micro air blower and the dehumidification switch is arranged in the panel. According to the utility model, the finger vein module can be quickly blow-dried when water vapor is condensed on the finger vein module, so that the condition of finger vein recognition failure is avoided.

The utility model discloses a front panel assembly and a door lock. The front panel assembly comprises a machine body, a sealing shell and a vein recognition module. Wherein the machine body is provided with an accommodating cavity; the sealing shell is arranged in the containing cavity, the sealing shell is provided with a sealing cavity and an identification hole, the identification hole is communicated with the sealing cavity, and a light-transmitting part is formed in the position, corresponding to the identification hole, of the machine body; the vein recognition module is arranged in the sealing cavity and corresponds to the recognition hole. According to the technical scheme of the utility model, the stability of user identification can be improved.

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.

SOLUTION: An artery-vein identification device 12 comprises: an oxygen saturation acquisition unit 70 configured to acquire oxygen saturation of blood in a needle hub 24 holding a needle 14 inserted into a blood vessel; a movement speed acquisition unit 72 configured to acquire the movement speed of the blood level moving within the needle hub; and a determination unit 74 configured to determine, based on the oxygen saturation and the movement speed, whether the blood vessel punctured by the needle is an artery or a vein.SELECTED DRAWING: Figure 5

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 utility model relates to a miniaturized vein recognition module and a B pillar plaque integrated with the same, the miniaturized vein recognition module comprises a camera module, a controller module and a microswitch module, the controller module comprises a PCBA, the PCBA is provided with an MCU component, an SOC component and an RGB lamp in an integrated manner, the MCU component is connected with the microswitch module, and the MCU component is connected with the microswitch module. The microswitch module wakes up the vein recognition module to be powered on through manual contact and pressing, the camera module recognizes and collects palm vein feature information and transmits the palm vein feature information to the controller module, vein extraction, enhancement and feature comparison are completed through an SOC component in the controller module, and a vein recognition result is transmitted to a vehicle machine through an MCU component. And the vehicle machine central control feeds back to unlock and lock the vehicle door. According to the utility model, the structure of the original module shell is eliminated, so that the size of the internal space of the required trim panel is relatively small, and the requirement of miniaturization of the frameless and frameless car door B column trim panel can be well met.

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.