earticle

영어

In this paper we propose one hybrid feature set filtering localization approach (HFSFLA) for iris recognition. Our HFSFLA method is different from the traditional iris localization method. Firstly we combine the advantages of both linear filtering method and non-linear filtering method, which can not only remove the noise and unwanted area but also keep the useful edge information of the iris image. Secondly, we propose feature set filtering localization to locate the iris precisely. Finally, we adopt one template matching method based on hamming distance deviation to recognize the iris information. Comparison experiments between the traditional localization method and the proposed HFSFLA are conducted on three iris databases. The experimental results show that the equal error rate and the correct recognition rate of the HFSFLA are better than those of the traditional localization method consistently in all iris data sets. And HFSFLA has high correct localization rate in the all three iris databases. It is a robust and rapid localization method.