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Geometric feature extraction by FTAs for finger-based biometrics system

Geometric feature extraction by FTAs for finger-based biometrics system

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In this study, a new geometric feature representation for a single finger geometry recognition based on infrared image is presented. The geometric representation is expressed based on the fingertip angles (FTA) measured from the right and the left finger edges. The extracted FTA feature is transformed into the frequency domain to form Fourier descriptor (FD) vector using discrete Fourier transform. The domain transformation is intended to make feature representation robust to the shifting, rotation and scaling variations. FD vectors from both right and the left contours are fused together to form a single row vector and principal component analysis is adopted to enhance the orthogonality between the FD components. The authors’ experimental results demonstrate the feasibility and the effectiveness of the proposed method.

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