Open AccessIntelligent Technique for Human Authentication using Fusion of Finger and Dorsal Hand Veins
Author(s) -
Mohamed Ahmed,
Abdel-Badeeh M. Salem
Publication year - 2021
Publication title -
wseas transactions on information science and applications
Language(s) - English
Resource type - Journals
eISSN - 2224-3402
pISSN - 1790-0832
DOI - 10.37394/23209.2021.18.12
Subject(s) - artificial intelligence , computer science , biometrics , pattern recognition (psychology) , preprocessor , adaptive histogram equalization , computer vision , classifier (uml) , region of interest , histogram , feature extraction , histogram equalization , image (mathematics)
Multimodal biometric systems have been widely used to achieve high recognition accuracy. This paper presents a new multimodal biometric system using intelligent technique to authenticate human by fusion of finger and dorsal hand veins pattern. We developed an image analysis technique to extract region of interest (ROI) from finger and dorsal hand veins image. After extracting ROI we design a sequence of preprocessing steps to improve finger and dorsal hand veins images using 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 Shandong University Machine Learning and Applications - Homologous Multi-modal Traits (SDUMLA-HMT) and Bosphorus Hand Vein Database. The achieved result for the fusion of both biometric traits was Correct Recognition Rate (CRR) is 96.8%.