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Quantitative evaluation methods of skin condition based on texture feature parameters

人工智能 模式识别(心理学) 计算机科学 像素 计算机视觉 人体皮肤 皮肤颜色 数学 遗传学 生物
作者
Hui Pang,Tianhua Chen,Xiaoyi Wang,Zhineng Chang,Siqi Shao,Jing Zhao
出处
期刊:Saudi Journal of Biological Sciences [Elsevier BV]
卷期号:24 (3): 514-518 被引量:18
标识
DOI:10.1016/j.sjbs.2017.01.021
摘要

In order to quantitatively evaluate the improvement of the skin condition after using skin care products and beauty, a quantitative evaluation method for skin surface state and texture is presented, which is convenient, fast and non-destructive. Human skin images were collected by image sensors. Firstly, the median filter of the 3 × 3 window is used and then the location of the hairy pixels on the skin is accurately detected according to the gray mean value and color information. The bilinear interpolation is used to modify the gray value of the hairy pixels in order to eliminate the negative effect of noise and tiny hairs on the texture. After the above pretreatment, the gray level co-occurrence matrix (GLCM) is calculated. On the basis of this, the four characteristic parameters, including the second moment, contrast, entropy and correlation, and their mean value are calculated at 45 ° intervals. The quantitative evaluation model of skin texture based on GLCM is established, which can calculate the comprehensive parameters of skin condition. Experiments show that using this method evaluates the skin condition, both based on biochemical indicators of skin evaluation methods in line, but also fully consistent with the human visual experience. This method overcomes the shortcomings of the biochemical evaluation method of skin damage and long waiting time, also the subjectivity and fuzziness of the visual evaluation, which achieves the non-destructive, rapid and quantitative evaluation of skin condition. It can be used for health assessment or classification of the skin condition, also can quantitatively evaluate the subtle improvement of skin condition after using skin care products or stage beauty.
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