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Hybrid threshold optimization between global image and local regions in image segmentation for melasma severity assessment

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Abstract

Melasma image segmentation plays a fundamental role for computerized melasma severity assessment. A method of hybrid threshold optimization between a given image and its local regions is proposed and used for melasma image segmentation. An analytic optimal hybrid threshold solution is obtained by minimizing the deviation between the given image and its segmented outcome. This optimal hybrid threshold comprises both local and global information around image pixels and is used to develop an optimal hybrid thresholding segmentation method. The developed method is firstly evaluated based on synthetic images and subsequently used for melasma segmentation and severity assessment. Statistical evaluations of experimental results based on real-world melasma images show that the proposed method outperforms other state-of-the-art thresholding segmentation methods for melasma severity assessment.

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Acknowledgments

We wish to acknowledge the funding support by A*STAR-NHG-NTU Skin Research Grant 2014 (SRG\(\backslash \)14011).

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Authors and Affiliations

  1. School of Information and Electronics, Beijing Institute of Technology, Beijing, 100081, People’s Republic of China

    Lei Sun

  2. School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore, 639798, Singapore

    Lei Sun, Wee Ser & Zhiping Lin

  3. School of Computer Engineering, Nanyang Technological University, Singapore, 639798, Singapore

    Feng Lin

  4. National Skin Center, Singapore, 308205, Singapore

    Evelyn Yuxin Tay, Emily Yiping Gan & Tien Guan Thng

  5. Interdisciplinary Graduate School, Nanyang Technological University, Singapore, 639798, Singapore

    Yunfeng Liang

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  1. Yunfeng Liang
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  2. Lei Sun
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  3. Wee Ser
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  4. Feng Lin
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  5. Evelyn Yuxin Tay
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  7. Tien Guan Thng
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  8. Zhiping Lin
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Correspondence to Lei Sun.

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Liang, Y., Sun, L., Ser, W. et al. Hybrid threshold optimization between global image and local regions in image segmentation for melasma severity assessment. Multidim Syst Sign Process 28, 977–994 (2017). https://doi.org/10.1007/s11045-015-0375-y

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  • DOI: https://doi.org/10.1007/s11045-015-0375-y

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