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Advancements in Fuzzy Clustering Algorithms for Image Processing: A Comprehensive Review and Future Directions

In: Advances in Data Clustering

Author

Listed:
  • Vatsala Anand

    (Chitkara University, Chitkara University Institute of Engineering and Technology)

  • Deepika Koundal

    (University of Eastern Finland
    University of Petroleum & Energy Studies, School of Computer Science
    Ho Chi Minh City Open University)

  • Thongchai Surinwarangkoon

    (Suan Sunandha Rajabhat University, Department of Computer Business, College of Innovation and Management)

  • Kittikhun Meethongjan

    (Suan Sunandha Rajabhat University, Department of Apply Science, Faculty of Science and Technology)

Abstract

Fuzzy clustering algorithms have emerged as powerful tools for various image processing tasks, owing to their ability to handle uncertainties and ambiguities inherent in image data. This chapter provides a comprehensive review of recent advancements in fuzzy clustering algorithms for image processing, focusing on applications such as image classification, texture analysis, segmentation of remote sensing images, and object recognition. Specifically, we discuss the principles and applications of fuzzy clustering in image classification, texture analysis, and segmentation tasks, highlighting the advantages and limitations of popular algorithms such as fuzzy C-means (FCM), spatial fuzzy C-means (SFCM), and intuitionistic fuzzy C-means (IFCM). Furthermore, we present a comparative analysis of these algorithms based on their performance metrics and suitability for different image processing tasks. Finally, we identify open challenges and propose potential future research directions in fuzzy clustering for image processing, including handling high-dimensional data, integration with deep learning techniques, scalability, interpretability, and addressing complex image structures.

Suggested Citation

  • Vatsala Anand & Deepika Koundal & Thongchai Surinwarangkoon & Kittikhun Meethongjan, 2024. "Advancements in Fuzzy Clustering Algorithms for Image Processing: A Comprehensive Review and Future Directions," Springer Books, in: Fadi Dornaika & Denis Hamad & Joseph Constantin & Vinh Truong Hoang (ed.), Advances in Data Clustering, chapter 0, pages 201-217, Springer.
    • Handle: RePEc:spr:sprchp:978-981-97-7679-5_11
    DOI: 10.1007/978-981-97-7679-5_11
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