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A Comparative Study Among Segmentation Techniques for Skin Disease Detection Systems

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Proceedings of International Conference on Trends in Computational and Cognitive Engineering

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1309))

Abstract

Skin disorders are serious health problems for people. An automatic mobile-oriented skin disease detection system with offline or online is extremely essential for detecting skin diseases and serving patient treatment plans. For any image-based detection as well as recognition task, useful features are playing an important role. But the extraction of essential features is seriously dependent on the segmentation of disease-affected region, which ultimately hampers the detection accuracy sensitivity and specificity. In this paper, we have described a comparative study on various segmentation algorithms that are applied to extract the lesion part from the skin images for detecting diseases. Available methods are evaluated based on both qualitative and quantitative perspectives. Besides, we have pointed out some challenges of skin disease detection which need special attention of researchers, such as the availability of extensive datasets, well-defined efficient segmentation algorithms, and mobile-friendly computation environment.

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Authors and Affiliations

  1. Department of Public Health and Informatics, Jahangirnagar University, Savar, Dhaka, Bangladesh

    Md. Al Mamun

  2. Department of Computer Science and Engineering, Jahangirnagar University, Savar, Dhaka, Bangladesh

    Mohammad Shorif Uddin

Authors
  1. Md. Al Mamun
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  2. Mohammad Shorif Uddin
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Correspondence to Md. Al Mamun .

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Editors and Affiliations

  1. Jahangirnagar University, Dhaka, Bangladesh

    M. Shamim Kaiser

  2. National Institute for Materials Science, Tsukuba, Japan

    Anirban Bandyopadhyay

  3. Nottingham Trent University, Nottingham, UK

    Mufti Mahmud

  4. Amity University, Jaipur, Rajasthan, India

    Kanad Ray

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Al Mamun, M., Uddin, M.S. (2021). A Comparative Study Among Segmentation Techniques for Skin Disease Detection Systems. In: Kaiser, M.S., Bandyopadhyay, A., Mahmud, M., Ray, K. (eds) Proceedings of International Conference on Trends in Computational and Cognitive Engineering. Advances in Intelligent Systems and Computing, vol 1309. Springer, Singapore. https://doi.org/10.1007/978-981-33-4673-4_14

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