Multimodal biometric system combining left and right palmprints. Issue 1 (17th September 2019)

• Record Type: Journal Article
• Authors: Taouche, Chérif; Belhadef, Hacene
• Is Part Of: Information discovery and delivery. Volume 48:Issue 1(2020)
• Page Start: 2
• Page End: 13
• Publication Date: 2019-09-17
• Subjects: Multimodal biometrics -- Feature selection -- Local descriptor -- Palmprint recognition -- Feature fusion -- Genetic algorithms -- BSA; Information retrieval -- Periodicals; Document delivery -- Periodicals; Digital libraries -- Periodicals; Information storage and retrieval systems -- Periodicals; 025.524
• DOI: 10.1108/IDD-01-2019-0011
• Languages: English
• ISSNs: 2398-6247

Abstract

Abstract : Purpose: Palmprint recognition is a very interesting and promising area of research. Much work has already been done in this area, but much more needs to be done to make the systems more efficient. In this paper, a multimodal biometrics system based on fusion of left and right palmprints of a person is proposed to overcome limitations of unimodal systems. Design/methodology/approach: Features are extracted using some proposed multi-block local descriptors in addition to MBLBP. Fusion of extracted features is done at feature level by a simple concatenation of feature vectors. Then, feature selection is performed on the resulting global feature vector using evolutionary algorithms such as genetic algorithms and backtracking search algorithm for a comparison purpose. The benefits of such step selecting the relevant features are known in the literature, such as increasing the recognition accuracy and reducing the feature set size, which results in runtime saving. In matching step, Chi-square similarity measure is used. Findings: The resulting feature vector length representing a person is compact and the runtime is reduced. Originality/value: Intensive experiments were done on the publicly available IITD database. Experimental results show a recognition accuracy of 99.17 which prove the effectiveness and robustness of the proposed multimodal biometrics system than other unimodal and multimodal biometrics systems.