Study on Objectively Evaluating Skin Aging According to Areas of Skin Texture_Journal of Biomedical Engineering

Authors：

SHANGaixian ^1,2 , GANPing ¹ , HELing ² , SUNLu ¹ , LIQiannan ¹ , JIANGZheng ¹ ,  HEXiangqian ¹

1. Laboratory of Forensic Medicine and Biomedicine Information, Chongqing Medical University, Chongqing 400016, China;
2. Department of Radiology, Affiliated Children's Hospital, Chongqing Medical University, Chongqing 400016, China;

Corresponding author：

HEXiangqian, Email: hexiangqian@gmail.com

Keywords：

skin texture; image processing; evaluating; skin aging

DOI：

10.7507/1001-5515.20150026

Video：

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Abstract Full text Figures/Tables Video References Cited by

Skin aging principles play important roles in skin disease diagnosis, the evaluation of skin cosmetic effect, forensic identification and age identification in sports competition, etc. This paper proposes a new method to evaluate the skin aging objectively and quantitatively by skin texture area. Firstly, the enlarged skin image was acquired. Then, the skin texture image was segmented by using the iterative threshold method, and the skin ridge image was extracted according to the watershed algorithm. Finally, the skin ridge areas of the skin texture were extracted. The experiment data showed that the average areas of skin ridges, of both men and women, had a good correlation with age (the correlation coefficient r of male was 0.938, and the correlation coefficient r of female was 0.922), and skin texture area and age regression curve showed that the skin texture area increased with age. Therefore, it is effective to evaluate skin aging objectively by the new method presented in this paper.

Citation： SHANGaixian, GANPing, HELing, SUNLu, LIQiannan, JIANGZheng, HEXiangqian. Study on Objectively Evaluating Skin Aging According to Areas of Skin Texture. Journal of Biomedical Engineering, 2015, 32(1): 142-145. doi: 10.7507/1001-5515.20150026 Copy

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8.	李利, MAC-MARY S, MARSAUT D, et al.白种人女性皮肤纹理与年龄和部位相关性研究[J].中华医学美学美容杂志, 2004, 10(1):15-19.
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10.	GUINOT C, MALVY D J, AMBROISINE L, et al. Relative contribution of intrinsic vs extrinsic factors to skin aging as determined by a validated skin age score[J]. Arch Dermatol, 2002, 138(11): 1454-1460.
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13.	董振, 蒲立新, 董方杰.基于改进分水岭算法和凹点搜索的乳腺癌粘连细胞分割[J].生物医学工程学杂志, 2013, 30(4):692-696.
14.	VINCENT L, SOILLE P. Watersheds in digital spaces: an efficient algorithm based on immersion simulations[J]. IEEE Trans Pattern Anal Mach Intell, 1993, 13(6): 583-598.
15.	CHEN X. Skin lesion segmentation by an adaptive watershed flooding approach[D]. USA: University of Missouri Rolla, 2007.
16.	SADRI A R, ZEKRI M, SADRI S, et al. Impulse noise cancellation of medical images using wavelet networks and median filters[J]. J Med Signals Sensors, 2012, 2(1): 25-37.
17.	BURY H, A. The morphological top-hat operator generalized to multi-channel images[C]//Proceedings of the 17th International Conference on Pattern Recognition, Cambridge: 2004: 672-675.
18.	BOUST C, BRETTEL H, VIENOT F, et al. Color enhancement of digital images by experts and preference judgments by observers[J]. J Imagi Sci Technol, 2006, 50(1): 1-11.

1. KOHL E, STEINBAUER J, LANDTHALER M, et al. Journal of the European academy of dermatology and venereology[J]. Skin Ageing, 2011, 25(8): 873-884.
2. GILCHREST B. A review of skin ageing and its medical therapy[J]. British J Dermatol, 1996, 135(6): 867-875.
3. 李利, MAC-MARY S, HUMBERT P.活体皮肤表面纹理无创性研究进展[J].国外医学:皮肤性病学分册, 2004, 30(5):291-293.
4. GAO Q, HU LW, WANG Y, et al. Skin texture parameters of the dorsal hand in evaluating skin aging in China[J]. Skin Res Technol, 2011, 17(4): 420-426.
5. FIELDER M, MEIER W D, HOPPE U. Texture analysis of the surface of the human skin[J]. Skin Pharmacol, 1995, 8(5): 252-265.
6. FISCHER T W, WIGGER-ALBERTI W, ELSNER P. Direct and non-direct measurement techniques for analysis of skin surface topography[J]. Skin Pharmacol Appl Skin Physiol, 1999, 12(1-2): 1-11.
7. LAGARDE J M, ROUVRAIS C, BLACK D. Topography and anisotropy of the skin surface with ageing[J]. Skin Res Technol, 2005, 11(2): 110-119.
8. 李利, MAC-MARY S, MARSAUT D, et al.白种人女性皮肤纹理与年龄和部位相关性研究[J].中华医学美学美容杂志, 2004, 10(1):15-19.
9. REXBYE H, PETERSEN I, JOHANSENS M, et al. Influence of environmental factors on facial ageing[J]. Age Ageing, 2006, 35(2): 110-115.
10. GUINOT C, MALVY D J, AMBROISINE L, et al. Relative contribution of intrinsic vs extrinsic factors to skin aging as determined by a validated skin age score[J]. Arch Dermatol, 2002, 138(11): 1454-1460.
11. RAFAEL C, GONZALEZ R E, Woods. Digital?image?processing[M]. 2nd ed. Beijing: Publishing House of Electronics Industry of China, 2007: 449-452.
12. ALI M R. Realization of the contrast limited adaptive histogram equalization(CLAHE)for real-time image enhancement[J]. J Signal Process Syst, 2004, 38(1): 35-44.
13. 董振, 蒲立新, 董方杰.基于改进分水岭算法和凹点搜索的乳腺癌粘连细胞分割[J].生物医学工程学杂志, 2013, 30(4):692-696.
14. VINCENT L, SOILLE P. Watersheds in digital spaces: an efficient algorithm based on immersion simulations[J]. IEEE Trans Pattern Anal Mach Intell, 1993, 13(6): 583-598.
15. CHEN X. Skin lesion segmentation by an adaptive watershed flooding approach[D]. USA: University of Missouri Rolla, 2007.
16. SADRI A R, ZEKRI M, SADRI S, et al. Impulse noise cancellation of medical images using wavelet networks and median filters[J]. J Med Signals Sensors, 2012, 2(1): 25-37.
17. BURY H, A. The morphological top-hat operator generalized to multi-channel images[C]//Proceedings of the 17th International Conference on Pattern Recognition, Cambridge: 2004: 672-675.
18. BOUST C, BRETTEL H, VIENOT F, et al. Color enhancement of digital images by experts and preference judgments by observers[J]. J Imagi Sci Technol, 2006, 50(1): 1-11.

Journal of Biomedical Engineering

Study on Objectively Evaluating Skin Aging According to Areas of Skin Texture

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