6 results about "Hand vein" patented technology

Embodiments of the present application disclose a file processing method and device, electronic equipment and a storage medium. The method comprises: when a file access request is received, obtaining a hand vein feature corresponding to a target subject; if the hand vein feature is consistent with a stored vein feature associated with a target vehicle, calling a to-be-matched icon password corresponding to the stored vein feature; if a to-be-verified icon password corresponding to a trigger operation is consistent with the to-be-matched icon password, determining that decryption of a target file corresponding to the file access request is successful, and displaying the target file. The present application solves the problem in the prior art that data is encrypted and decrypted based on a single finger vein feature, and the data is easily leaked due to a low encryption coefficient, thereby improving the difficulty coefficient of data decryption and achieving the effect of ensuring data security.

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 application relates to the technical field of back-of-hand vein recognition, and discloses a back-of-hand or palm vein image key point and ROI positioning method based on an improved UNet, which comprises the following steps: S1, collecting an experimental system machine on site; S2, self-building a data set; S3, establishing a UNet model; S4, establishing a residual module; S5, an improved UNet model for back-of-hand or palm vein image key point positioning; S6, using an ROI calculation method to calculate the extraction of a region of interest; and S7, evaluating the model. Near-infrared imaging technology is used to acquire a back-of-hand or palm vein image. The improved UNet model can realize back-of-hand or palm key point positioning (ROI extraction) on a non-contact back-of-hand or palm vein image, and is suitable for actual deployment on a low-resource platform such as an edge embedded system.

This invention discloses a method and device for full hand vein biometric recognition to prevent spoofing attacks, relating to the fields of full hand vein recognition, biometric information recognition, and identity authentication. The method includes: Step 1, image acquisition and detection: acquiring a frontal hand image covering the palm and finger areas, ensuring the presence of a palm and a real living person in the frontal hand image; Step 2, ROI extraction: extracting the palm vein ROI and the multi-finger ROI; Step 3, feature extraction: extracting palm vein features and features of the four fingers, and generating corresponding feature hash codes; Step 4, feature matching: first matching the palm vein features, then matching the four finger features; similarity comparison is achieved by calculating the Hamming distance between the feature hash codes; Step 5, score fusion: calculating the matching scores for the palm vein features and the four finger features respectively, then performing Tanh normalization on the matching scores, and finally fusing the normalized matching scores to obtain the final recognition result.

A system and method of identifying a person using images captured from a single camera. The camera is used to image facial features and iris patterns. A person is identified by matching both the facial features and the iris patterns to patterns of previously enrolled people. The images captured by the camera are initially analyzed to sort prime images from obscured images. The prime images are processed to increase the resolution. Facial feature data and the iris pattern data are compared to data in at least one database to match data and identify the person. An illumination system is used that illuminates the person being imaged with infrared or near infrared light. The illumination system is designed to reduce specularities in captured images. The illumination system also enables the light to better penetrate the skin of the hand, if hand vein patterns are imaged.

The application discloses a hand vein recognition method and device fusing depth information and relates to the technical field of vein recognition. The method comprises the following steps: collecting a target image group; the target image group comprises two hand vein images with parallax; respectively pre-processing the two hand vein images to obtain two vein texture images; matching the two vein texture images to obtain a depth image; superimposing the depth image and the two vein texture images to obtain a three-channel image to be recognized; inputting the three-channel image to be recognized into a feature parameter extraction model to extract feature parameters, and obtaining feature parameters to be recognized; calculating target Euclidean distances between the feature parameters to be recognized and sample feature parameters corresponding to each sample data group; and determining an individual corresponding to the target image group according to the sizes of the target Euclidean distances. The application can improve the reliability of vein recognition and avoid cracking of a vein recognition device.