Blurred palmprint recognition based on stable-feature extraction using a Vese-Osher decomposition model.

ABSTRACT: As palmprints are captured using non-contact devices, image blur is inevitably generated because of the defocused status. This degrades the recognition performance of the system. To solve this problem, we propose a stable-feature extraction method based on a Vese-Osher (VO) decomposition model to recognize blurred palmprints effectively. A Gaussian defocus degradation model is first established to simulate image blur. With different degrees of blurring, stable features are found to exist in the image which can be investigated by analyzing the blur theoretically. Then, a VO decomposition model is used to obtain structure and texture layers of the blurred palmprint images. The structure layer is stable for different degrees of blurring (this is a theoretical conclusion that needs to be furth

SUBMITTER: Hong D 

PROVIDER: S-EPMC4081781 | biostudies-literature | 2014

REPOSITORIES: biostudies-literature