Performance Comparison of Image Transforms for Palm Print Recognition with Fractional Coefficients of Transformed Palm Print Images

摘要

The paper presents performance comparison of palm print recognition techniques based on fractional coefficients of transformed palm print image using six different transforms like Sine, Cosine, Walsh, Slant, Hartley and Haar. 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 neglecting the low frequency coefficients in transformed palm print images. Six image transforms and 13 ways of taking fractional coefficients result into total 78 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 ratio (FAR) and genuine acceptance ratio (GAR). The experimental results in Sine, Walsh, Haar, Cosine transform have shown performance improvement in palm print identification using fractional coefficients of transformed images. In all Cosine transform at fractional coefficients of 0.78% gives best performance as indicated by higher GAR value. Thus the task of speeding up the process of palm print identification with better performance is achieved making it more suitable for real time applications.