Design and Implementation of a Robust Palm Biometrics Recognition and Verification System

Complete design and implementation of a robust palm biometrics recognition and verification system has been presented. The paper attempts to scientifically develop a comprehensive set of hand geometry features and develop an original algorithm from a fundamental level to robustly compute a selected set of features so as to minimize palm placement effect. These features are combined with chrominance features, to achieve recognition and verification accuracy, significant with respect to the current state in palm biometrics research. The algorithm has been kept robust, simple and computationally efficient while the implementation is relatively inexpensive. The experiments on recognition, Principal Components Analysis (PCA) and verification, on a dataset of 100 users strongly confirm the utility of robustly calculating a comprehensive set of scientifically selected hand geometry features. The results uncover the potential of hand geometry features and confirm that the system can be used in medium to high security environments.