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Color-Based Image Segmentation by Means of a Robust Intuitionistic Fuzzy C-means Algorithm

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Abstract

To yield well-suited image segmentation results, conventional clustering algorithms depend on customized hand-crafted features as well as an appropriate initialization process. This latter aspect is a mandatory pre-requisite for convergence of the algorithm, in other words, its efficiency impacts the quality of the result. In this work, we introduce an Intuitionistic Fuzzy C-Means clustering algorithm enhanced by means of Robust Statistics, which develops an outstanding image segmentation based on a basic feature such as the color information, and it requires a reduced iteration number to converge. The non-parametric Lorentzian Redescending M-estimator is used both at initialization and iterative stages of the clustering algorithm; since, it behaves such as a robust location estimator when the centroid vector is computed, and as a weighting when the membership matrix is updated. With the fusion of both techniques, we can guarantee that the introduced clustering algorithm can efficiently develop the task of segmentation of color images and pattern recognition processes. The robustness and effectiveness of this proposal is verified by experiments on the natural color images BSDS500 dataset, as well as a simulated dataset corrupted with atypical data.

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Acknowledgements

The authors are grateful to the editors and the reviewers for their valuable comments. The authors thank the Consejo Nacional de Ciencia y Tecnología, Tecnológico Nacional de México/Centro Nacional de Investigación y Desarrollo Tecnológico for their support of this research through the project “Sistema Embebido para asistencia de conducción basado en Lógica Difusa Tipo-2”.

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Authors and Affiliations

  1. Departamento de Ciencias Computacionales, Tecnológico Nacional de México/CENIDET, Cuernavaca, Morelos, México

    Dante Mújica-Vargas

  2. Unidad Profesional Interdisciplinaria de Ingeniería Campus Hidalgo, Instituto Politécnico Nacional, Pachuca, San Agustín Tlaxiaca, Hidalgo, México

    Jean Marie Vianney Kinani

  3. Sección de Estudios de Posgrado e Investigación, Esime Azcapotzalco, Instituto Politécnico Nacional, Ciudad de México, México

    José de Jesús Rubio

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  1. Dante Mújica-Vargas
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  2. Jean Marie Vianney Kinani
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  3. José de Jesús Rubio
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Correspondence to Dante Mújica-Vargas.

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Mújica-Vargas, D., Kinani, J.M.V. & Rubio, J.d. Color-Based Image Segmentation by Means of a Robust Intuitionistic Fuzzy C-means Algorithm. Int. J. Fuzzy Syst. 22, 901–916 (2020). https://doi.org/10.1007/s40815-020-00824-x

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  • DOI: https://doi.org/10.1007/s40815-020-00824-x

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