Skin Visualization Using Smartphone and Deep Learning in the Beauty Industry

被引:1
|
作者
Hasegawa, Makoto [1 ]
Matsuo, Rui [2 ]
机构
[1] Tokyo Denki Univ, Sch Engn, Tokyo 1208551, Japan
[2] Tokyo Denki Univ, Grad Sch Engn, Tokyo 1208551, Japan
关键词
beauty industry; skin care; deep learning; smartphone; cycleGAN;
D O I
10.1587/transinf.2021EDK0004
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Human skin visualization in the beauty industry with a smart-phone based on deep learning was discussed. Skin was photographed with a medical camera that could simultaneously capture RGB and UV images of the same area. Smartphone RGB images were converted into versions similar to medical RGB and UV images via a deep learning method called cycle-GAN, which was trained with the medical and the smartphone images. After converting the smartphone image into a version similar to a medical RGB image using cycle-GAN, the processed image was also converted into a pseudo-UV image via a deep learning method called U-NET. Hidden age spots were effectively visualized by this image. RGB and UV images similar to medical images can be captured with a smartphone. Provided the neural network on deep learning is trained, a medical camera is not required.
引用
收藏
页码:68 / 77
页数:10
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