Aiming at defects of low accuracy and easy to by affected by complexity of fingerprint deformation of existing fingerprint matching algorithm segmented fingerprint matching algorithm based on multi-wavelets theory fusion strategy is proposed. Combines with multi-wavelets fusion theory and segmented theory. In this method

fingerprint images are decomposed based on multi-wavelets to extract the feature vectors

then the feature vectors is fused into a general feature vector based on Dempster-Shafer（ DS） evidential theory. Normalized partial energyweighted-mutual-information matching is introduced as new similarity measures in first-local-matching step. Then changeable sized boundary box method is applied to carry out the second-global-matching step. Experimental results show that the proposed algorithm improves accuracy

while also be slightly influenced by the deformation factor of the fingerprint.