Palm detecting and key point location method based on deep learning

Abstract

The invention discloses a palm detecting and key point location method based on deep learning. The palm detecting and key point location method based on deep learning particularly includes the following steps of 1, collecting training samples; 2, building network models, wherein a CNN feature extraction network, an RPN candidate area extraction network and a judgment network are built; 3, trainingthe network models, wherein the CNN feature extraction network, the RPN candidate area extraction network and the judgment network are initialized; 4, building a detection model, wherein the CNN feature extraction network, the RPN candidate area extraction network and the judgment network form a Faster R-CNN detection network; 5, detecting the palm and location key points. According to the palm detecting and key point location method based on deep learning, the Faster R-CNN detection framework which has optimal performance and accuracy at present is adopted, compared with a Fast R-CNN, a RPNis adopted to replace a Selective Search method to extract candidate areas, the RPN is completely built in the whole target detection framework, therefore, the speed of extracting the candidate areasis increased, and at the same time, the detection accuracy is improved.

Description

technical field [0001] The invention belongs to the technical field of palm vein recognition, in particular to a method for palm detection and key point positioning based on deep learning. Background technique [0002] In terms of biometric recognition technology, image processing technology is generally used to collect biometric images, preprocess them, locate regions of interest and extract features, and then perform matching and recognition. In the technical details of image processing and feature extraction, there will be a variety of technical solutions, the purpose of which is to improve the speed and accuracy of recognition. [0003] Both palmprint and palm vein recognition need to extract a Region of Interest (ROI) from the collected palm image, so as to obtain a stable ROI as the recognition region. Extracting the ROI requires identifying the outline of the palm and locating key points, and extracting the ROI based on multiple key points. The quality of ROI extrac...

AI Technical Summary

Problems solved by technology

[0005] The above method is insufficient in the contour extraction and key point positioning of the palm image, in terms of speed and accuracy

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