This paper proposes a Hybrid Improved Bacterial Swarm (HIBS) optimization algorithm for the minimization of Equal Error Rate (EER) as a performance measure in a hand-based multimodal biometric authentication system. The hybridization of the algorithm was conducted by incorporating Bacterial Foraging Optimization (BFO) and Particle Swarm Optimization (PSO) algorithm to mitigate weaknesses in slow and premature convergence. | Journal of ICT, 18, No. 2 (April) 2019, pp: 123–141 How to cite this article: Shanmugasundaram, K., Mohmed, A. S. A., & Ruhaiyem, N. I. R. (2019). Hybrid improved bacterial swarm optimization algorithm for hand-based multimodal biometric authentication system. Journal of Information and Communication Technology, 18(2), 123-141. HYBRID IMPROVED BACTERIAL SWARM OPTIMIZATION ALGORITHM IN HAND-BASED MULTIMODAL BIOMETRIC AUTHENTICATION SYSTEM Karthikeyan Shanmugasundaram, Ahmad Sufril Azlan Mohmed & Nur Intan Raihana Ruhaiyem School of Computer Sciences, Universiti Sains Malaysia, Malaysia karthik_mcamtech@;sufril@;intanraihana@ ABSTRACT This paper proposes a Hybrid Improved Bacterial Swarm (HIBS) optimization algorithm for the minimization of Equal Error Rate (EER) as a performance measure in a hand-based multimodal biometric authentication system. The hybridization of the algorithm was conducted by incorporating Bacterial Foraging Optimization (BFO) and Particle Swarm Optimization (PSO) algorithm to mitigate weaknesses in slow and premature convergence. In the proposed HIBS algorithm, the slow convergence of BFO algorithm was mitigated by using the random walk procedure of Firefly algorithm as an adaptive varying step size instead of using fixed step size. Concurrently, the local optima trap (. premature convergence) of PSO algorithm was averted by using mutation operator. The HIBS algorithm was tested using benchmark functions and compared against classical BFO, PSO and other hybrid algorithms like Genetic AlgorithmBacterial Foraging Optimization (GA-BFO), Genetic AlgorithmParticle Swarm Optimization (GA-PSO) and other BFO-PSO algorithms to prove its exploration and exploitation ability. It was observed from the experimental results that the EER values, after the influence of the proposed HIBS algorithm, dropped to and from and for the right and left hand images of the Bosphorus database, respectively. The .
