The fusion of multispectral palmprints using the information set based features and classifier

Abstract

This paper presents three texture features, viz., topothesy-fractal dimension, Hanman transform, and structure function based transform for the multispectral palmprint based authentication. It introduces the notion of information set originating from the Hanman–Anirban entropy. Using information set, Hanman transform features are derived. The topothesy-fractal dimension features arise from the structure function on representing the intensity variation on the texture surface. The structure function based transform features are derived from both structure function and the Hanman transform. Apart from the feature extraction, the fuzzy classifier based on the information processing is also developed. A novel score level fusion is proposed using Triangular-norms and Triangular-conorms. Thus the paper’s contribution is three-fold: i) New features for multispectral palmprint, ii) novel classifier for authentication, and iii) score level fusion for improving the accuracy. The rigorous experimental results certify that the proposed approaches make a substantial improvement in the authentication accuracy and outperform the contemporary approaches.