Otsu Based Optimal Multilevel Image Thresholding Using Firefly Algorithm

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...

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Main Authors: N. Sri Madhava Raja, V. Rajinikanth, K. Latha
Format: Article
Language:English
Published: Wiley 2014-01-01
Series:Modelling and Simulation in Engineering
Online Access:http://dx.doi.org/10.1155/2014/794574
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author N. Sri Madhava Raja
V. Rajinikanth
K. Latha
author_facet N. Sri Madhava Raja
V. Rajinikanth
K. Latha
author_sort N. Sri Madhava Raja
collection DOAJ
description 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.
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spelling doaj-art-701140b1322f4fb186d7f0331c94b02c2025-02-03T06:48:36ZengWileyModelling and Simulation in Engineering1687-55911687-56052014-01-01201410.1155/2014/794574794574Otsu Based Optimal Multilevel Image Thresholding Using Firefly AlgorithmN. Sri Madhava Raja0V. Rajinikanth1K. Latha2Department of Electronics and Instrumentation Engineering, St. Joseph’s College of Engineering, Chennai 600 119, IndiaDepartment of Electronics and Instrumentation Engineering, St. Joseph’s College of Engineering, Chennai 600 119, IndiaDepartment of Instrumentation Engineering, Anna University, MIT Campus, Chennai 600 044, IndiaHistogram 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.http://dx.doi.org/10.1155/2014/794574
spellingShingle N. Sri Madhava Raja
V. Rajinikanth
K. Latha
Otsu Based Optimal Multilevel Image Thresholding Using Firefly Algorithm
Modelling and Simulation in Engineering
title Otsu Based Optimal Multilevel Image Thresholding Using Firefly Algorithm
title_full Otsu Based Optimal Multilevel Image Thresholding Using Firefly Algorithm
title_fullStr Otsu Based Optimal Multilevel Image Thresholding Using Firefly Algorithm
title_full_unstemmed Otsu Based Optimal Multilevel Image Thresholding Using Firefly Algorithm
title_short Otsu Based Optimal Multilevel Image Thresholding Using Firefly Algorithm
title_sort otsu based optimal multilevel image thresholding using firefly algorithm
url http://dx.doi.org/10.1155/2014/794574
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