Palm Print Identification Using Fractional Coefficients of Sine/Walsh/Slant Transformed Palm Print Images

Abstract

AbstractThe paper presents performance comparison of palm print identification techniques based on fractional coefficients of transformed palm print image using three different transforms like Sine, Walsh and Slant. In transform domain, the energy of image gets accumulated towards high frequency region; this characteristic of image transforms is exploited here to reduce the feature vector size of palm print images by selecting these high frequency coefficients in transformed palm print images. Three image transforms and 12 ways of taking fractional coefficients result into total 36 palm print identification methods. A database of 2350 palm print images is used as a test bed for performance comparison of the proposed palm print identification methods with help of false acceptance rate (FAR) and genuine acceptance rate (GAR). The experimental results in Sine and Walsh transform have shown performance improvement in palm print identification using fractional coefficients of transformed images. In all Sine transform at fractional coefficients of 0.78% gives best performance as indicated by higher GAR value. Thus the task of speeding up palm print identification with better performance is achieved to make it more suitable for real time applications.KeywordsPalm PrintBiometricSine TransformWalsh TransformSlant Transform