An objective skin‐type classification based on noninvasive biophysical parameters

2021 ◽  
Author(s):  
Ji‐In Seo ◽  
Hye In Ham ◽  
Ji Hwoon Baek ◽  
Min Kyung Shin
Keyword(s):  
Skin Type ◽  
Biophysical Parameters ◽  
Type Classification

New method for large‐scale facial skin sebum quantification and skin type classification

2020 ◽  
Author(s):  
Jingjing Qin ◽  
Liyuan Qiao ◽  
Jingjing Hu ◽  
Jichao Xu ◽  
Le Du ◽  
...  
Keyword(s):  
Large Scale ◽  
Skin Type ◽  
New Method ◽  
Facial Skin ◽  
Type Classification

scholarly journals Facial Skincare Products’ Recommendation with Computer Vision Technologies

Electronics ◽  
2022 ◽  
Vol 11 (1) ◽  
pp. 143
Author(s):  
Ting-Yu Lin ◽  
Hung-Tse Chan ◽  
Chih-Hsien Hsia ◽  
Chin-Feng Lai
Keyword(s):  
Computer Vision ◽  
Recommendation System ◽  
Payment System ◽  
Skin Type ◽  
Identification System ◽  
Electronic Payment ◽  
Identity Verification ◽  
Finger Vein ◽  
Electronic Payment System ◽  
Type Classification

Acne is a skin issue that plagues many young people and adults. Even if it is cured, it leaves acne spots or acne scars, which drives many individuals to use skincare products or undertake medical treatment. On the contrary, the use of inappropriate skincare products can exacerbate the condition of the skin. In view of this, this work proposes the use of computer vision (CV) technology to realize a new business model of facial skincare products. The overall framework is composed of a finger vein identification system, skincare products’ recommendation system, and electronic payment system. A finger vein identification system is used as identity verification and personalized service. A skincare products’ recommendation system provides consumers with professional skin analysis through skin type classification and acne detection to recommend skincare products that finally improve skin issues of consumers. An electronic payment system provides a variety of checkout methods, and the system will check out by finger-vein connections according to membership information. Experimental results showed that the equal error rate (EER) comparison of the FV-USM public database on the finger-vein system was the lowest and the response time was the shortest. Additionally, the comparison of the skin type classification accuracy was the highest.

Cosmetic Skin Type Classification Using CNN With Product Recommendation

2021 ◽  
Author(s):  
Arya Kothari ◽  
Dipam Shah ◽  
Taksh Soni ◽  
Sudhir Dhage
Keyword(s):  
Skin Type ◽  
Product Recommendation ◽  
Type Classification
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