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Evaluation of Entropy-Based Segmentation Techniques for Automated Skin Disease Detection

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Book cover Proceeding of International Conference on Intelligent Communication, Control and Devices

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 479))

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Abstract

Image segmentation is a crucial part of medical imaging technology. Threshold-based image segmentation is very effective for medical images. A good segmentation helps in correct diagnosis. In this paper, entropy-based thresholding is used for automatic segmentation of hypo and hyperpigmented skin disease. Here threshold values are selected based on Shannon and Gini entropy. A comparison study with Otsu and Fuzzy C-Means (FCM) method is carried out based on rand index (RI) to prove efficiency of entropy-based thresholding. The rand index value indicates that Gini entropy-based thresholding is the best choice for hypo and hyperpigmented skin diseases segmentation.

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References

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Acknowledgments

I would like to thank Dr. Sanjib Chowdhury, Consultant Dermatologist, Haldia Port Haspital, Haldia, West Bengal for providing me with the dataset. I also want to thank West Bengal University of Technology’s TEQIP II program and DST FIST with reference number FIST/ETI/296/2011.

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Authors and Affiliations

  1. Department of Computer Science and Engineering, West Bengal University of Technology, BF 142 Salt Lake Sector 1, Kolkata, India

    Ishita Bhakta &  Santanu Phadikar

Authors
  1. Ishita Bhakta
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  2. Santanu Phadikar
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Correspondence to Ishita Bhakta .

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Editors and Affiliations

  1. Electronics, Instrumentation & Control, University of Petroleum & Energy Studies, Dehradun, Uttarakhand, India

    Rajesh Singh

  2. Electronics, Instrumentation and Control, Univer. of Petroleum and Energy Studies, Dehradun, Uttarakhand, India

    Sushabhan Choudhury

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Ishita Bhakta, Santanu Phadikar (2017). Evaluation of Entropy-Based Segmentation Techniques for Automated Skin Disease Detection. In: Singh, R., Choudhury, S. (eds) Proceeding of International Conference on Intelligent Communication, Control and Devices . Advances in Intelligent Systems and Computing, vol 479. Springer, Singapore. https://doi.org/10.1007/978-981-10-1708-7_39

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  • DOI: https://doi.org/10.1007/978-981-10-1708-7_39

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-1707-0

  • Online ISBN: 978-981-10-1708-7

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