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Context based image segmentation using antlion optimization and sine cosine algorithm

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Abstract

Multilevel thresholding (MTH) is one of the most commonly used approaches to perform segmentation on images. However, as most methods are based on the histogram of the image to be segmented, MTH methods only consider the occurrence frequency of certain intensity level disregarding all spatial information. Contextual information can help to enhance the quality of the segmented image as it considers not only the value of the pixel but also its vicinity. The energy curve was designed to bring spatial information into a curve with the same properties as the histogram. In this paper, two recently proposed Evolutionary Computational Algorithms (ECAs) are coupled with two classical thresholding criteria to perform MTH over the energy curve. The selected ECAs are the Antlion Optimizer (ALO) and the Sine Cosine Algorithm (SCA). The proposed methods are evaluated intensively regarding quality, and a statistical analysis is presented to compare the results of the algorithms against similar approaches. Experimental evidence encourages the use ALO for MTH while it concludes that SCA does not outperform other ECAs form the state-of-the-art.

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Acknowledgements

The first author acknowledges to Mexican Government for partially supporting this research under the program for New Full Time Professors 2017 of PRODEP. The authors second and fourth acknowledge to CONACYT for the grants 298283 and 234148, respectively.

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Authors and Affiliations

  1. División de Electrónica y Computación, Universidad de Guadalajara, CUCEI, Av. Revolución 1500, Guadalajara, JAL, México

    Diego Oliva & Noé Ortega-Sánchez

  2. Dpto. Ingeniería del Software e Inteligencia Artificial, Facultad Informática, Universidad Complutense de Madrid, 28040, Madrid, Spain

    Salvador Hinojosa

  3. School of Computer Science and Technology, Wuhan University of Technology, Wuhan, China

    Mohamed Abd Elaziz

  4. Department of Mathematics, Faculty of Science, Zagazig University, Zagazig, Egypt

    Mohamed Abd Elaziz

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  1. Diego Oliva
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  2. Salvador Hinojosa
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  3. Mohamed Abd Elaziz
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  4. Noé Ortega-Sánchez
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Correspondence to Diego Oliva.

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All authors are affiliated with International Research Team.

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Oliva, D., Hinojosa, S., Elaziz, M.A. et al. Context based image segmentation using antlion optimization and sine cosine algorithm. Multimed Tools Appl 77, 25761–25797 (2018). https://doi.org/10.1007/s11042-018-5815-x

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