VO Decomposition Model Method for Blurred Palmprint Recognition

In order to solve the problem that during the collection of palmprint images by using noncontact device, it is easy to generate the defocus blurred image and degrade the performance of the recognition system;a blurred palmprint recognition method based on VO decomposition was proposed.Firstly, Gaussian defocus degradation model was established for simulating the image blur.There exist stable features in the process of image blurring by analyzing the blur theory.Such stable feature was considered as the structure layer of image from the perspective of image layering.Thereby, the structure layer of blurred image was obtained by using VO decomposition model.We used the blocked histogram of oriented gradient to extract the stable features from the structure layer in order to improve the distinguishability of feature.Finally, normalized correlation classifier was used to measure the similarity of palmprint.The experimental results show that the recognition accuracy of the proposed method is superior and stable in the PolyU palmprint database and the Blurred-PolyU palmprint database, moreover, the equal error rate (EER:0.309 1%) of the proposed method is lower than the classical high-performance algorithms in Blurred-PolyU palmprint database.The identification of time is less 1.3s at a time, which meets the real-time requirement.The effectiveness and real-time of the proposed method is in this paper verified.