Research On Small Area Fingerprint Image Recognition Method Collected By PMOLED

As the most widely used biometric identification technology,fingerprint identification technology has been widely used in the identification of intelligent door locks,punch cards and other electronic devices.As the fingerprint collector becomes more miniaturized and portable,the collected fingerprint image becomes smaller and smaller.The application of traditional fingerprint identification methods for small area fingerprint image recognition will lead to a significant reduction in correct recognition rate.At the same time,LED lights are the most frequently used backlight source for optical fingerprint collectors,which has the disadvantages of high power consumption and uneven backlight.Therefore,this paper designs an optical fingerprint acquisition system using PMOLED(passive matrix OLED)screen,and studies the recognition method of small area fingerprint image from image processing and deep learning.The main work of this paper is as follows:(1)An optical fingerprint acquisition system based on self luminous PMOLED screen is designed.Aiming at the problems of the original image collected by the system,such as the interference of the screen luminous pixels,the average value elimination method is used to reduce the noise of the original data,which greatly reduces the screen interference signal.After normalization,low-pass filtering,image enhancement,binarization and refinement,the clear single pixel small area fingerprint image is obtained.(2)A small area fingerprint recognition method based on topology splicing is proposed.Firstly,two kinds of minutiae feature points,bifurcation point and endpoint point,are extracted from the thinned fingerprint image,and the direction field angle of each minutiae feature point is calculated.Then,the two fingerprint images are matched by feature points,and the matching feature points are connected by topological structure.Finally,the optimal rotation and translation parameters are obtained by using the sum of Euclidean distances between matched feature points Product fingerprint stitching,improve the correct acceptance rate.(3)A small area fingerprint identification method based on improved residual network and convolutional attention mechanism is proposed.The single residual block in the residual network is improved to three residual block types,and the residual blocks are rearranged by different stacking methods to reduce the impact of too many nonlinear activation functions.Then convolution attention mechanism is added to the improved residual network,and the extracted fingerprint image features are weighted by convolution attention mechanism.This method reduces the convergence time of network training and testing,and improves the accuracy of testing.The experimental results show that the optical fingerprint acquisition system designed by PMOLED is reliable and effective,and the small area fingerprint image recognition method based on topology splicing achieves 99.57%and 99.65%correct recognition rates in the self built database and the reconstructed FVC2002DB2 fingerprint database,respectively.The small area fingerprint identification method based on improved residual network and convolutional attention mechanism achieves 98.15%and 98.69%test accuracy respectively in the self built database and the reconstructed FVC2002DB2 fingerprint database,which proves the effectiveness of this method and able to meets the application requirements of intelligent products.