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Improved Digital Image Enhancement Filters Based on Type-2 Neuro-Fuzzy Techniques Read chapter Read first chapter

2013 | OriginalPaper | Chapter

3. Hybrid BBO-DE Algorithms for Fuzzy Entropy-Based Thresholding

Authors : Ilhem Boussaïd, Amitava Chatterjee, Patrick Siarry, Mohamed Ahmed-Nacer

Published in: Computational Intelligence in Image Processing

Publisher: Springer Berlin Heidelberg

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Abstract

This chapter shows how a recently proposed stochastic optimization algorithm, called biogeography-based optimization (BBO), can be efficiently employed for development of three-level thresholding-based image segmentation. This technique is utilized to determine suitable thresholds utilizing a fuzzy entropy-based fitness function, which the optimization procedure attempts to maximize. The chapter demonstrates how improved BBO-based strategies, employing hybridizations with differential evolution (DE) algorithms, can be employed to incorporate diversity in the basic BBO algorithm that can help the optimization algorithm avoid getting trapped at local optima and seek the global optimum in a more efficient manner. Several such hybrid BBO-DE algorithms have been utilized for this optimum thresholding-based image segmentation procedure. A detailed implementation analysis for a popular set of well-known benchmark images has been carried out to qualitatively and quantitatively demonstrate the utility of the proposed hybrid BBO-DE optimization algorithm.

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Literature
1.
Acharya, T., Ray, A.K.: Image Processing—Principles and Applications. Wiley-Interscience, New Jersey (2005)CrossRef
2.
3.
Boussaïd, I., Chatterjee, A., Siarry, P., Ahmed-Nacer, M.: Two-stage update biogeography-based optimization using differential evolution algorithm (dbbo). Comput. Oper. Res. 38, 1188–1198 (2011)MathSciNetMATHCrossRef
4.
Chang, C.I., Du, Y., Wang, J., Guo, S.M., Thouin, P.D.: Survey and comparative analysis of entropy and relative entropy thresholding techniques. IEE Proc. Vis. Image Signal Process. 153(6), 837–850 (2006)CrossRef
5.
Cheng, H., Chen, J., Li, J.: Threshold selection based on fuzzy c-partition entropy approach. Pattern Recogn. 31(7), 857–870 (1998)CrossRef
6.
Cover, T.M., Thomas, J.A.: Elements of Information Theory. Wiley-Interscience, New York (1991)MATHCrossRef
7.
Darwin, C.: Origin of Species. Gramercy, New York (1995)
8.
De Luca, A., Termini, S.: A definition of a non-probabilistic entropy in the setting of fuzzy sets theory. Inf. Control 20, 301–312 (1972)MATHCrossRef
9.
10.
Freixenet, J., Muñoz, X., Raba, D., Martí, J., Cufí, X.: Yet another survey on image segmentation: region and boundary information integration. In: Proceedings of the 7th European Conference on Computer Vision-Part III, ECCV ’02, pp. 408–422. Springer-Verlag, London, UK (2002)
11.
Gong, W., Cai, Z., Ling, C.: DE/BBO: a hybrid differential evolution with biogeography-based optimization for global numerical optimization. Soft Comput. Fusion Found. Methodol. Appl. (2010)
12.
Kapur, J., Sahoo, P., Wong, A.: A new method for gray-level picture thresholding using the entropy of the histogram. Comput. Vision Graph. Image Process. 29(3), 273–285 (1985)CrossRef
13.
Kaufmann, A.: Introduction to the Theory of Fuzzy Subsets. Academic Press, New York (1975)MATH
14.
Kaufmann, A.: Measures of Fuzzy Information. Mathematical Sciences Trust Society, New Delhi (1977)
15.
Klir, G.J., St. Clair, U., Yuan, B.: Fuzzy Set Theory: Foundations and Applications. Prentice-Hall, Inc., Upper Saddle River (1997)
16.
Levine, M., Nazif, A.: Dynamic measurement of computer generated image segmentations. IEEE Trans. Pattern Anal. Mach. Intell. 7, 155–164 (1985)CrossRef
17.
MacArthur, R., Wilson, E.: The Theory of Biogeography. Princeton University Press, Princeton (1967)
18.
Noman, N., Iba, I.: Accelerating differential evolution using an adaptive local search. IEEE Trans. Evol. Comput. 12(1), 107–125 (2008)CrossRef
19.
Pal, N.R., Pal, S.K.: Higher order fuzzy entropy and hybrid entropy of a set. Inf. Sci. 61, 211–231 (1992)MATHCrossRef
20.
Pal, N.R., Pal, S.K.: A review on image segmentation techniques. Pattern Recognit. 26(9), 1277–1294 (1993)CrossRef
21.
Price, K.V., Storn, R.M., Lampinen, J.A.: Differential Evolution: A Practical Approach to Global Optimization. Natural Computing Series. Springer, Berlin (2005)
22.
Pun, T.: A new method for gray-level picture thresholding using the entropy of histogram. Signal Process. 2(3), 223–237 (1980)CrossRef
23.
Pun, T.: Entropic thresholding, a new approach. Comput. Graph. Image Process. 16(3), 210–239 (1981)CrossRef
24.
Sahoo, P.K., Soltani, S., Wong, A.K., Chen, Y.C.: A survey of thresholding techniques. Comput. Vision Graph. Image Process. 41, 233–260 (1988)CrossRef
25.
Sahoo, P.K., Wilkins, C., Yeager, J.: Threshold selection using Renyi’s entropy. Pattern Recognit. 30(i1), 71–84 (1997)MATHCrossRef
26.
Sezgin, M., Sankur, B.: Survey over image thresholding techniques and quantitative performance evaluation. J. Electron. Imaging 13(1), 146–168 (2004)CrossRef
27.
Shannon, C.E.: A Mathematical theory of communication. CSLI Publications (1948)
28.
Simon, D.: Biogeography-based optimization. IEEE Trans. Evol. Comput. 12, 702–713 (2008)CrossRef
29.
Storn, R.M., Price, K.V.: Differential evolution—a simple and efficient heuristic for global optimization over continuous spaces. J. Glob. Optim. 11, 341–359 (1997)MathSciNetMATHCrossRef
30.
Tao, W., Jin, H., Liu, L.: Object segmentation using ant colony optimization algorithm and fuzzy. entropy 28(7), 788–796 (2007)
31.
Tao, W., Tian, J., Liu, J.: Image segmentation by three-level thresholding based on maximum fuzzy entropy and genetic algorithm. Pattern Recogn. Lett. 24(16), 3069–3078 (2003)CrossRef
32.
Tobias, O., Seara, R.: Image segmentation by histogram thresholding using fuzzy sets. IEEE Trans. Image Process. 11(12), 1457–1465 (2002)CrossRef
33.
34.
Wallace, A.R.: The Geographical Distribution of Animals (two volumes). Adamant Media Corporation, Boston (2005)
35.
36.
Zhao, M., Fu, A., Yan, H.: A technique of three-level thresholding based on probability partition and fuzzy 3-partition. IEEE Trans. Fuzzy Syst. 9(3), 469–479 (2001)CrossRef
Metadata
Title
Hybrid BBO-DE Algorithms for Fuzzy Entropy-Based Thresholding
Authors
Ilhem Boussaïd
Amitava Chatterjee
Patrick Siarry
Mohamed Ahmed-Nacer
Copyright Year
2013
Publisher
Springer Berlin Heidelberg
Book
Computational Intelligence in Image Processing

Print ISBN: 978-3-642-30620-4

Electronic ISBN: 978-3-642-30621-1

Copyright Year: 2013

DOI
https://doi.org/10.1007/978-3-642-30621-1_3

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