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Modelling and Simulation in Engineering
Volume 2014, Article ID 794574, 17 pages
Research Article

Otsu Based Optimal Multilevel Image Thresholding Using Firefly Algorithm

1Department of Electronics and Instrumentation Engineering, St. Joseph’s College of Engineering, Chennai 600 119, India
2Department of Instrumentation Engineering, Anna University, MIT Campus, Chennai 600 044, India

Received 22 January 2014; Accepted 12 May 2014; Published 15 June 2014

Academic Editor: Jing-song Hong

Copyright © 2014 N. Sri Madhava Raja et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Histogram based multilevel thresholding approach is proposed using Brownian distribution (BD) guided firefly algorithm (FA). A bounded search technique is also presented to improve the optimization accuracy with lesser search iterations. Otsu’s between-class variance function is maximized to obtain optimal threshold level for gray scale images. The performances of the proposed algorithm are demonstrated by considering twelve benchmark images and are compared with the existing FA algorithms such as Lévy flight (LF) guided FA and random operator guided FA. The performance assessment comparison between the proposed and existing firefly algorithms is carried using prevailing parameters such as objective function, standard deviation, peak-to-signal ratio (PSNR), structural similarity (SSIM) index, and search time of CPU. The results show that BD guided FA provides better objective function, PSNR, and SSIM, whereas LF based FA provides faster convergence with relatively lower CPU time.