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Rényi’s Entropy and Bat Algorithm Based Color Image Multilevel Thresholding

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Book cover Machine Intelligence and Signal Analysis

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 748))

Abstract

Colored satellite images are difficult to segment due to their low illumination, dense features, uncertainties, etc. Rényi’s entropy is a famous entropy criterion that provides excellent outputs in bi-level thresholding based segmentation. But such method suffers lack of accuracy, inefficiency, and instability when extended to perform color image multilevel thresholding. Therefore, a new color image multilevel segmentation strategy based on Bat algorithm and Rényi’s entropy is proposed in this paper to determine the optimal threshold values more efficiently. The experiments are conducted on four real satellite images and two well-known test images at different threshold levels. The study shows that the proposed algorithm obtains good quality and adequate segmented results more effectively as compared to other multilevel thresholding algorithms such as Rényi’s-PSO and Otsu-PSO.

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References

  1. Otsu, N.: Threshold selection method from gray-level histograms. IEEE Trans. Syst. Man Cybern. 9(1), 62–66 (1979)

    Article  MathSciNet  Google Scholar 

  2. Tsai, W.H.: Moment-preserving thresolding: a new approach. Comput. Vis. Gr. Image Process. 29(3), 377–393 (1985)

    Article  Google Scholar 

  3. Kapur, J.N., Sahoo, P.K., Wong, A.K.: A new method for gray-level picture thresholding using the entropy of the histogram. Comput. Vis. Gr. Image Process. 29(3), 273–285 (1985)

    Article  Google Scholar 

  4. Lim, Y.W., Lee, S.U.: On the color image segmentation algorithm based on the thresholding and the fuzzy c-means techniques. Pattern Recogn. 23(9), 935–952 (1990)

    Article  Google Scholar 

  5. Li, C.H., Lee, C.K.: Minimum cross entropy thresholding. Pattern Recogn. 26(4), 617–625 (1993)

    Article  Google Scholar 

  6. Sahoo, P., Wilkins, C., Yeager, J.: Threshold selection using Renyi’s entropy. Pattern Recogn. 30(1), 71–84 (1997)

    Article  Google Scholar 

  7. Sahoo, P.K., Arora, G.: A thresholding method based on two-dimensional Renyi’s entropy. Pattern Recogn. 37(6), 1149–1161 (2004)

    Article  Google Scholar 

  8. Wang, S., Chung, F.L.: Note on the equivalence relationship between Renyi-entropy based and Tsallis-entropy based image thresholding. Pattern Recogn. Lett. 26(14), 2309–2312 (2005)

    Article  Google Scholar 

  9. Sarkar, S., Das, S., Chaudhuri, S.S.: Hyper-spectral image segmentation using Rényi’s entropy based multi-level thresholding aided with differential evolution. Expert Syst. Appl. 50, 120–129 (2016)

    Article  Google Scholar 

  10. Sarkar, S., Das, S., Chaudhuri, S.S.: A multilevel color image thresholding scheme based on minimum cross entropy and differential evolution. Pattern Recogn. Lett. 54, 27–35 (2015)

    Article  Google Scholar 

  11. Sağ, T., Çunkaş, M.: Color image segmentation based on multiobjective artificial bee colony optimization. Appl. Soft Comput. 34, 389–401 (2015)

    Article  Google Scholar 

  12. Beevi, S., Nair, M.S., Bindu, G.R.: Automatic segmentation of cell nuclei using Krill Herd optimization based multi-thresholding and localized active contour model. Biocybern. Biomed. Eng. 36(4), 584–596 (2016)

    Article  Google Scholar 

  13. Rajinikanth, V., Couceiro, M.S.: RGB histogram based color image segmentation using firefly algorithm. Proc. Comput. Sci. 46, 1449–1457 (2015)

    Article  Google Scholar 

  14. Pare, S., Bhandari, A.K., Kumar, A., Singh, G.K., Khare, S.: Satellite image segmentation based on different objective functions using genetic algorithm: a comparative study. In: IEEE International Conference on Digital Signal Processing (DSP), pp. 1–13. IEEE (2015)

    Google Scholar 

  15. Bhandari, A.K., Kumar, A., Singh, G.K.: Modified artificial bee colony based computationally efficient multilevel thresholding for satellite image segmentation using Kapur’s, Otsu and Tsallis functions. Expert Syst. Appl. 42(3), 1573–1601 (2015)

    Article  Google Scholar 

  16. Bhandari, A.K., Singh, V.K., Kumar, A., Singh, G.K.: Cuckoo search algorithm and wind driven optimization based study of satellite image segmentation for multilevel thresholding using Kapur’s entropy. Expert Syst. Appl. 41(7), 3538–3560 (2014)

    Article  Google Scholar 

  17. Pare, S., Kumar, A., Bajaj, V., Singh, G.K.: A multilevel color image segmentation technique based on cuckoo search algorithm and energy curve. Appl. Soft Comput. 47, 76–102 (2016)

    Article  Google Scholar 

  18. Pare, S., Kumar, A., Bajaj, V., Singh, G.K.: An efficient method for multilevel color image thresholding using cuckoo search algorithm based on minimum cross entropy. Appl. Soft Comput. 61, 570–592 (2017)

    Article  Google Scholar 

  19. Bhandari, A.K., Kumar, A., Singh, G.K.: Tsallis entropy based multilevel thresholding for colored satellite image segmentation using evolutionary algorithms. Expert Syst. Appl. 42(22), 8707–8730 (2015)

    Article  Google Scholar 

  20. Bhandari, A.K., Kumar, A., Chaudhary, S., Singh, G.K.: A novel color image multilevel thresholding based segmentation using nature inspired optimization algorithms. Expert Syst. Appl. 63, 112–133 (2016)

    Article  Google Scholar 

  21. Pare, S., Bhandari, A.K., Kumar, A., Singh, G.K.: An optimal color image multilevel thresholding technique using grey-level co-occurrence matrix. Expert Syst. Appl. 87, 335–362 (2017)

    Article  Google Scholar 

  22. Pare, S., Bhandari, A.K., Kumar, A., Bajaj, V.: Backtracking search algorithm for color image multilevel thresholding. Signal Image Video Process 1–8 (2017)

    Google Scholar 

  23. Yang, X.S.: A new metaheuristic bat-inspired algorithm. In: Nature Inspired Cooperative Strategies for Optimization (NICSO 2010), pp. 65–74 (2010)

    Google Scholar 

  24. Hasançebi, O., Teke, T., Pekcan, O.: A bat-inspired algorithm for structural optimization. Comput. Struct. 128, 77–90 (2013)

    Article  Google Scholar 

  25. Hasançebi, O., Carbas, S.: Bat inspired algorithm for discrete size optimization of steel frames. Adv. Eng. Softw. 67, 173–185 (2014)

    Article  Google Scholar 

  26. Alihodzic, A., Tuba, M.: Bat algorithm (BA) for image thresholding. In: Recent Researches in Telecommunications, Informatics, Electronics and Signal Processing, pp. 17–19 (2013)

    Google Scholar 

  27. Alihodzic, A., Tuba, M.: Improved bat algorithm applied to multilevel image thresholding. The Sci. World J. (2014)

    Google Scholar 

  28. Ye, Z.W., Wang, M.W., Liu, W., Chen, S.B.: Fuzzy entropy based optimal thresholding using bat algorithm. Appl. Soft Comput. 31, 381–395 (2015)

    Article  Google Scholar 

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Authors and Affiliations

  1. Indian Institute of Information Technology Design and Manufacturing, Jabalpur, Jabalpur, 482005, Madhya Pradesh, India

    S. Pare & A. Kumar

  2. National Institute of Technology, Patna, Patna, 800005, Bihar, India

    A. K. Bhandari

  3. Indian Institute of Technology Roorkee, Roorkee, 247667, Uttarakhand, India

    G. K. Singh

Authors
  1. S. Pare
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  2. A. K. Bhandari
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  3. A. Kumar
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  4. G. K. Singh
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Corresponding author

Correspondence to S. Pare .

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Editors and Affiliations

  1. Discipline of Mathematics, Indian Institute of Technology Indore, Simrol, Madhya Pradesh, India

    M. Tanveer

  2. Discipline of Electrical Engineering, Indian Institute of Technology Indore, Simrol, Madhya Pradesh, India

    Ram Bilas Pachori

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Pare, S., Bhandari, A.K., Kumar, A., Singh, G.K. (2019). Rényi’s Entropy and Bat Algorithm Based Color Image Multilevel Thresholding. In: Tanveer, M., Pachori, R. (eds) Machine Intelligence and Signal Analysis. Advances in Intelligent Systems and Computing, vol 748. Springer, Singapore. https://doi.org/10.1007/978-981-13-0923-6_7

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