31 October 2016 Evaluation and recognition of skin images with aging by support vector machine
Author Affiliations +
Abstract
Aging is a very important issue not only in dermatology, but also cosmetic science. Cutaneous aging involves both chronological and photoaging aging process. The evaluation and classification of aging is an important issue with the medical cosmetology workers nowadays. The purpose of this study is to assess chronological-age-related and photo-age-related of human skin. The texture features of skin surface skin, such as coarseness, contrast were analyzed by Fourier transform and Tamura. And the aim of it is to detect the object hidden in the skin texture in difference aging skin. Then, Support vector machine was applied to train the texture feature. The different age’s states were distinguished by the support vector machine (SVM) classifier. The results help us to further understand the mechanism of different aging skin from texture feature and help us to distinguish the different aging states.
© (2016) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Liangjun Hu, Shulian Wu, Hui Li, "Evaluation and recognition of skin images with aging by support vector machine", Proc. SPIE 10024, Optics in Health Care and Biomedical Optics VII, 100242X (31 October 2016); doi: 10.1117/12.2245949; https://doi.org/10.1117/12.2245949
PROCEEDINGS
10 PAGES


SHARE
Back to Top