Title: Multisensor biometric evidence fusion of face and palmprint for person authentication using Particle Swarm Optimisation (PSO)
Authors: R. Raghavendra, Ashok Rao, G. Hemantha Kumar
Addresses: Department of Studies in Computer Science, University of Mysore, Mysore 570006, India. ' Department of E&C, Channabasaveshwara Institute of Technology, Gubbi, Tumkur 572216, India. ' Department of Studies in Computer Science, University of Mysore, Mysore 570006, India
Abstract: This paper presents a novel biometric sensor fusion technique for face and palmprint images using Particle Swarm Optimisation (PSO). The proposed method can be visualised in the following steps: we first decompose the face and palmprint image obtained from different sensors using wavelet transformation and then, we employ PSO to select most informative wavelet coefficients from face and palmprint to produce a new fused image. We then employed Kernel Direct Discriminant Analysis (KDDA) for feature extraction and the decision about accept/reject is carried out using Nearest Neighbour Classifier (NNC). Extensive experiments carried out on a virtual multimodal biometric database of 250 users indicate the efficacy of the proposed method.
Keywords: multimodal biometrics; image fusion; match score level fusion; face images; palmprint images; PSO; particle swarm optimisation; sensor fusion; multisensor fusion; wavelet coefficients; feature extraction.
International Journal of Biometrics, 2010 Vol.2 No.1, pp.19 - 33
Published online: 15 Dec 2009 *Full-text access for editors Access for subscribers Purchase this article Comment on this article