Fingerprint characterization using SVD features

Our objective of this project is to apply the theory of linear algebra called “singular value decomposition (SVD)” to digital image processing, specifically for fingerprint images verification. For optimal recognition, we proceed in two steps. In the first step, we begin by identifying the fingerprint features with SVD approach. In the second step, the classification accuracy of the proposed approach is evaluated with Back Propagation Neural Network (BPNN) classifier. I have implemented many extensive experiments, they prove that the fingerprint classification based on a novel SVD features and the BPNN give better results in fingerprint verification than several other features and methods.