Finger vein recognition using Integrated Responses of Texture features

Abstract

The finger vein recognition system is a secure and a reliable system with the advantage of robustness against malicious attacks. It is more convenient to operate this biometric feature than other biometric features such as facial and iris recognition system. The paper proposes a unique technique to find the local and the global features using Integrated Responses of Texture (IRT) features from finger veins which improves the overall accuracy of the system and is invariant to rotations. The segmentation of region of interest at different resolution levels makes the system highly efficient. The lower resolution data gives the overall global features and the higher resolution data gives the distinct local features. The complete feature set is descriptive in nature and reduces the Equal Error Rate to 0.523%. The Multi-Support Vector Machine (Multi-SVM) is used to classify and match the obtained results. The experimental results indicate that the system is highly accurate with an accuracy of 94%.