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Image-based facial pore detection and visualization in skin health evaluation

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Abstract

The role of health information visualization and visual analytics processes is gaining importance. The facial pore feature is one of the crucial indicators of skin health evaluation. However, pores are tiny, which is difficult to detect and analyze based on the digital picture. In this paper, we aim to visualize facial pores by fabricating data to display their different roughness levels. First, we presented an image-based facial pore detection algorithm that combines the characteristics of skin pigment distribution and optimal scale. Second, based on the pore detection result, we proposed a P-DBSCAN (Pore density-based spatial clustering of applications with noise) algorithm that integrates pore characteristics. Because the local saliences of pores and interferences are different at the biological perspective, the interferences can be considered as noisy data in the scheme of well-known DBSCAN algorithm. As a result, the proposed algorithm determines two essential thresholds for facial pore detection and visualization, and makes it possible to improve the detection accuracy and accomplish visualization. On that basis, an index to objectively evaluate the roughness of skin pores was established by using the optimal scales in SIFT. The experiment results suggest improved accuracy of pore detection, and the facial pore visualization presents pore information directly and efficiently.

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Acknowledgements

This work was presented in the paper is partially supported by grants from the Natural Science Foundation of Tianjin (No.16JCYBJC42000, No.18JCYBJC85100), MOE (Ministry of Education in China) Project of Humanities and Social Sciences (No.19YJA630046). The statements made herein are solely the responsibility of the authors.

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Authors and Affiliations

  1. Department of Information Science and Technology, Tianjin University of Finance and Economics, Tianjin, China

    Zhen Wang & Ruoxuan Li

  2. College of Intelligence and Computing, Tianjin University, Tianjin, China

    Chongke Bi

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  1. Zhen Wang
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  2. Ruoxuan Li
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  3. Chongke Bi
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Correspondence to Zhen Wang.

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Wang, Z., Li, R. & Bi, C. Image-based facial pore detection and visualization in skin health evaluation. J Vis 22, 1039–1055 (2019). https://doi.org/10.1007/s12650-019-00581-6

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  • DOI: https://doi.org/10.1007/s12650-019-00581-6

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