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Modelling and Simulation in Engineering
Volume 2014, Article ID 794574, 17 pages
http://dx.doi.org/10.1155/2014/794574
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.

Citations to this Article [41 citations]

The following is the list of published articles that have cited the current article.

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  • G. Hari Hara Sudhan, R. Ganesh Aravind, K. Gowri, and V. Rajinikanth, “Optic disc segmentation based on Otsu's thresholding and level set,” 2017 International Conference on Computer Communication and Informatics (ICCCI), pp. 1–5, . View at Publisher · View at Google Scholar
  • Silviu-Ioan Bejinariu, Hariton Costin, Florin Rotaru, Ramona Luca, and Cristina Diana Nita, “Automatic multi-threshold image segmentation using metaheuristic algorithms,” 2015 International Symposium on Signals, Circuits and Systems (ISSCS), pp. 1–4, . View at Publisher · View at Google Scholar
  • Rajinikanth, and Couceiro, “Multilevel segmentation of color image using Lévy driven BFO Algorithm,” ACM International Conference Proceeding Series, vol. 10-11-, 2014. View at Publisher · View at Google Scholar
  • A.K. Bhandari, A. Kumar, and G.K. Singh, “Modified artificial bee colony based computationally efficient multilevel thresholding for satellite image segmentation using Kapur’s, Otsu and Tsallis functions,” Expert Systems with Applications, 2014. View at Publisher · View at Google Scholar
  • A.K. Bhandari, A. Kumar, and G.K. Singh, “Tsallis Entropy based Multilevel Thresholding for Colored Satellite Image Segmentation using Evolutionary Algorithms,” Expert Systems with Applications, 2015. View at Publisher · View at Google Scholar
  • Amira Bouaziz, Amer Draa, and Salim Chikhi, “Artificial bees for multilevel thresholding of iris images,” Swarm and Evolutionary Computation, vol. 21, pp. 32–40, 2015. View at Publisher · View at Google Scholar
  • Suresh Manic, Rajinikanth, Sarath Ananthasivam, and Uma Suresh, “Design of controller in double feedback control loop - An analysis with heuristic algorithms,” Chemical Product and Process Modeling, vol. 10, no. 4, pp. 253–262, 2015. View at Publisher · View at Google Scholar
  • Devikumari, and Vijayan, “Decentralized PID controller design for 3x3 multivariable system using heuristic algorithms,” Indian Journal of Science and Technology, vol. 8, no. 15, 2015. View at Publisher · View at Google Scholar
  • V. Rajinikanth, and M.S. Couceiro, “RGB Histogram Based Color Image Segmentation Using Firefly Algorithm,” Procedia Computer Science, vol. 46, pp. 1449–1457, 2015. View at Publisher · View at Google Scholar
  • Madhava Rajaa, Arockia Sukanya, and Nikitaa, “Improved PSO based multi-level thresholding for cancer infected breast thermal images using otsu,” Procedia Computer Science, vol. 48, no. C, pp. 524–529, 2015. View at Publisher · View at Google Scholar
  • K. Sundaravadivu, S. Sivakumar, N. Hariprasad, K. Sundaravadivu, S. Sivakumar, and N. Hariprasad, “2DOF PID Controller Design for a Class of FOPTD Models - An Analysis with Heuristic Algorithms,” International Conference On Computer, Communication And Convergence (Iccc 2015), vol. 48, pp. 90–95, 2015. View at Publisher · View at Google Scholar
  • Rajinikanth, Couceiro, V. Rajinikanth, and M. S. Couceiro, “Optimal multilevel image threshold selection using a novel objective function,” Advances in Intelligent Systems and Computing, vol. 340, pp. 177–186, 2015. View at Publisher · View at Google Scholar
  • Abhinaya, and Sri Madhava Raja, “Solving multi-level image thresholding problem—an analysis with Cuckoo search algorithm,” Advances in Intelligent Systems and Computing, vol. 339, pp. 177–186, 2015. View at Publisher · View at Google Scholar
  • A.K. Bhandari, A. Kumar, S. Chaudhary, and G.K. Singh, “A Novel Color Image Multilevel thresholding based Segmentation using Nature Inspired Optimization Algorithms,” Expert Systems with Applications, 2016. View at Publisher · View at Google Scholar
  • Saad M. Darwish, “Combining firefly algorithm and Bayesian classifier: new direction for automatic multilabel image annotation,” IET Image Processing, 2016. View at Publisher · View at Google Scholar
  • N. Sri Madhava Raja, and Vishnupriya, “Kapur's entropy and Cuckoo search algorithm assisted segmentation and analysis of RGB images,” Indian Journal of Science and Technology, vol. 9, no. 17, 2016. View at Publisher · View at Google Scholar
  • Shilpa Suresh, and Shyam Lal, “An Efficient Cuckoo Search Algorithm based Multilevel Thresholding for Segmentation of Satellite Images Using Different Objective Functions,” Expert Systems with Applications, 2016. View at Publisher · View at Google Scholar
  • Padma, and Latha, “Multiple-loop PI controller design for tito system using Teaching Learning Based Optimization,” Indian Journal of Science and Technology, vol. 9, no. 12, 2016. View at Publisher · View at Google Scholar
  • Suresh Manic, Rajinikanth, and Krishna Priya, “Image multithresholding based on Kapur/Tsallis entropy and firefly algorithm,” Indian Journal of Science and Technology, vol. 9, no. 12, 2016. View at Publisher · View at Google Scholar
  • Salima Ouadfel, and Abdelmalik Taleb-Ahmed, “Social spiders optimization and flower pollination algorithm for multilevel image thresholding: A performance study,” Expert Systems with Applications, 2016. View at Publisher · View at Google Scholar
  • Rakoth Kandan Sambandam, and Sasikala Jayaraman, “Self-adaptive dragonfly based optimal thresholding for multilevel segmentation of digital images,” Journal of King Saud University - Computer and Information Sciences, 2016. View at Publisher · View at Google Scholar
  • Suresh Chandra Satapathy, Sri Madhava Raja, Rajinikanth, Amira S. Ashour, and Nilanjan Dey, “Multi-level image thresholding using Otsu and chaotic bat algorithm,” Neural Computing and Applications, pp. 1–23, 2016. View at Publisher · View at Google Scholar
  • Curtis Larimer, Eric Winder, Robert Jeters, Matthew Prowant, Ian Nettleship, Raymond Shane Addleman, and George T. Bonheyo, “A method for rapid quantitative assessment of biofilms with biomolecular staining and image analysis,” Analytical And Bioanalytical Chemistry, vol. 408, no. 3, pp. 999–1008, 2016. View at Publisher · View at Google Scholar
  • K. Sundaravadivu, C. Ramadevi, R. Vishnupriya, K. Sundaravadivu, C. Ramadevi, and R. Vishnupriya, “Design of Optimal Controller for Magnetic Levitation System Using Brownian Bat Algorithm,” Artificial Intelligence And Evolutionary Computations In Engineering Systems, Icaieces 2015, vol. 394, pp. 1321–1329, 2016. View at Publisher · View at Google Scholar
  • N. Siva Balan, A. Sadeesh Kumar, N. Sri Madhava Raja, Rajinikanth, N. Siva Balan, A. Sadeesh Kumar, N. Sri Madhava Raja, and V. Rajinikanth, “Optimal multilevel image thresholding to improve the visibility of Plasmodium sp. In blood smear images,” Advances in Intelligent Systems and Computing, vol. 397, pp. 563–571, 2016. View at Publisher · View at Google Scholar
  • Venkatesan Rajinikanth, N. Sri Madhava Raja, Suresh Chandra Satapathy, Venkatesan Rajinikanth, N. Sri Madhava Raja, and Suresh Chandra Satapathy, “Robust Color Image Multi-thresholding Using Between-Class Variance and Cuckoo Search Algorithm,” Information Systems Design And Intelligent Applications, Vol 1, India 2016, vol. 433, pp. 379–386, 2016. View at Publisher · View at Google Scholar
  • Sundaravadivu, Sadeeshkumar, and Nivethitha Devi, “Segmentation of noise stained gray scale images with Otsu and Firefly Algorithm,” Indian Journal of Science and Technology, vol. 9, no. 22, 2016. View at Publisher · View at Google Scholar
  • Palani T. Krishnan, Parvathavarthini Balasubramanian, and Chitra Krishnan, “Segmentation of Brain Regions by Integrating Meta Heuristic Multilevel Threshold with Markov Random Field,” Current Medical Imaging Reviews, vol. 12, no. 1, pp. 4–12, 2016. View at Publisher · View at Google Scholar
  • Seyed Jalaleddin Mousavirad, and Hossein Ebrahimpour-Komleh, “Multilevel image thresholding using entropy of histogram and recently developed population-based metaheuristic algorithms,” Evolutionary Intelligence, 2017. View at Publisher · View at Google Scholar
  • N. Sri MadhavaRaja, Rajinikanth, Suresh Chandra Satapathy, and Steven Lawrence Fernandes, “Otsu's multi-thresholding and active contour snake model to segment dermoscopy images,” Journal of Medical Imaging and Health Informatics, vol. 7, no. 8, pp. 1837–1840, 2017. View at Publisher · View at Google Scholar
  • Gandikota DIvya, Sundaravadivu, DIksha Uniyal, and Sivakumar, “Soft computing approach based segmentation and analysis of skin cancer,” 2017 International Conference on Computer Communication and Informatics, ICCCI 2017, 2017. View at Publisher · View at Google Scholar
  • Abinaya, Nilanjan Dey, Suresh Chandra Satapathy, Anitha, Bindhiya, and Rajinikanth, “RGB image multi-thresholding based on Kapur's entropy - A study with heuristic algorithms,” Proceedings of the 2017 2nd IEEE International Conference on Electrical, Computer and Communication Technologies, ICECCT 2017, 2017. View at Publisher · View at Google Scholar
  • Ortiz P. David, Daniel Sierra-Sosa, and Begoña García Zapirain, “Pressure ulcer image segmentation technique through synthetic frequencies generation and contrast variation using toroidal geometry,” BioMedical Engineering Online, vol. 16, no. 1, 2017. View at Publisher · View at Google Scholar
  • Adles Kouassi, Sié Ouattara, Jean-Claude Okaingni, Wognin J. Vangah, and Alain Clement, “A Semi-Vectorial Hybrid Morphological Segmentation of Multicomponent Images Based on Multithreshold Analysis of Multidimensional Compact Histogram,” Open Journal of Applied Sciences, vol. 07, no. 11, pp. 597–610, 2017. View at Publisher · View at Google Scholar
  • Daniel Sierra-Sosa, Adel Elmaghraby, Sofia Zahia, and Begonya Garcia-Zapirain, “Tissue classification and segmentation of pressure injuries using convolutional neural networks,” Computer Methods and Programs in Biomedicine, vol. 159, pp. 51–58, 2018. View at Publisher · View at Google Scholar
  • N. Sri Madhava Raja, S. L. Fernandes, Nilanjan Dey, Suresh Chandra Satapathy, and V. Rajinikanth, “Contrast enhanced medical MRI evaluation using Tsallis entropy and region growing segmentation,” Journal of Ambient Intelligence and Humanized Computing, 2018. View at Publisher · View at Google Scholar
  • V. Rajinikanth, Nilanjan Dey, Suresh Chandra Satapathy, and Amira S. Ashour, “An approach to examine magnetic resonance angiography based on Tsallis entropy and deformable snake model,” Future Generation Computer Systems, 2018. View at Publisher · View at Google Scholar
  • Nilanjan Dey, Venkatesan Rajinikanth, Amira Ashour, and João Manuel Tavares, “Social Group Optimization Supported Segmentation and Evaluation of Skin Melanoma Images,” Symmetry, vol. 10, no. 2, pp. 51, 2018. View at Publisher · View at Google Scholar
  • T.D. Varsha Shree, Revanth, N. Sri Madhava Raja, and Rajinikanth, “A Hybrid Image Processing Approach to Examine Abnormality in Retinal Optic Disc,” Procedia Computer Science, vol. 125, pp. 157–164, 2018. View at Publisher · View at Google Scholar
  • Kesavan Suresh Manic, Imad Saud Al Naimi, Feras N. Hasoon, and V. Rajinikanth, “Jaya Algorithm-Assisted Evaluation of Tooth Elements Using Digital Bitewing Radiography Images,” Computational Techniques for Dental Image Analysis, pp. 107–128, 2019. View at Publisher · View at Google Scholar