Personal Authentication Using Palmprint with Sobel Code, Canny Edge and Phase Congruency Feature Extraction Method

Palmprint recognition refers to recognizing a person on the basis of palmprint features. In this paper, we have proposed a palmprint based biometric authentication method with improvement in accuracy, so as to make it a real time palmprint authentication system. Several edge detection methods, Directional operator, Wavelet transform, Fourier transform etc. are available to extract line feature from the palmprint. In this paper, Sobel Code operators, Canny edge and Phase Congruency methods are applied to the palmprint image to extract palmprint features. The extracted Palmprint features are stored in Palmprint feature vector. The corresponding feature vectors are matched using sliding window with Hamming Distance similarity measurement method. In this paper, a Min Max Threshold Range (MMTR) method is proposed that helps in increasing overall system accuracy by reducing the False Acceptance Rate (FAR). The person authenticated by reference threshold is again verified by second level of authentication using MMTR method. Experimental results indicate that the MMTR method improves the False Acceptance Rate drastically. The accuracy improvement leads to proposed real time authentication system.