Robust Multimodal Handvein and Palmprint Based Verification System in the Presence of Salt and Pepper Noise

Abstract

Noise is a random signal that usually arises during electronic transmission, preprocessing, acquisition, faulty storage that distorts the original information of the image. Image can be deteriorated by various kinds of noises. In our work, we are proposing both the unimodal and multimodal biometric verification system adopting hand-based traits and we are also analyzing the robustness of the deployed system by adding salt and pepper noise that takes either maximum or minimum grey values. The experimentation is performed on multimodal preclassification and post classification techniques and the verification results are tabulated for standard threshold values at 0.01%, 0.1 %, 1 %.