Abstract
A novel cancelable palmprint templates generation scheme is proposed in this paper. Firstly, the Gabor filter and chaotic matrix are used to extract palmprint features. It is then arranged into a row vector and divided into equal size blocks. These blocks are converted to corresponding decimals and mapped to look up tables, forming final cancelable palmprint features based on the selected check bits. Finally, collaborative representation based classification with regularized least square is used for classification. Experimental results on the Hong Kong PolyU Palmprint Database verify that the proposed cancelable templates can achieve very high performance and security levels. Meanwhile, it can also satisfy the needs of real-time applications.
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