Multimodal Technique for Human Authentication Using Fusion of Palm and Dorsal Hand Veins

Abstract

AbstractMultimodal biometric systems have been widely used to achieve high recognition accuracy. This paper presents a new multimodal biometric system using an intelligent technique to authenticate human by fusion of palm and dorsal hand veins pattern. We developed an image analysis technique to extract region of interest (ROI) from palm and dorsal hand veins image. After extracting ROI we design a sequence of preprocessing steps to improve palm and dorsal hand veins images using Homomorphic, Median filter, Wiener filter and Contrast Limited Adaptive Histogram Equalization (CLAHE) to enhance vein image. Our smart technique is based on the following intelligent algorithms, namely; principal component analysis (PCA) algorithm for feature extraction and k-Nearest Neighbors (K-NN) classifier for matching operation. The database chosen was the CASIA Multi-Spectral Palmprint Image Database V1.0 and Bosphorus Hand Vein Database. The achieved result for the fusion of both biometric traits was Correct Recognition Rate (CRR) is 97.6% with FAlse Reject Rate (FRR) 2.4%.KeywordsBiometric systemsPattern recognitionIntelligent computingImage processingMachine learning