TY - JOUR
T1 - Scheme fuzzy approach to classify skin tonalities through geographic distribution
AU - Hernandez-Matamoros, Andres
AU - Fujita, Hamido
AU - Nakano-Miyatake, Mariko
AU - Perez-Meana, Hector
AU - Escamilla-Hernandez, Enrique
N1 - Publisher Copyright:
© 2019, Springer-Verlag GmbH Germany, part of Springer Nature.
PY - 2020/7/1
Y1 - 2020/7/1
N2 - One of the most significant current discussions in Computer Science is the skin recognition. Many papers have studied the skin detection using different techniques, artificial vision, machine learning, deep learning among others. Despite its long success, the skin recognition has several problems in use. However, there has been little discussion about generate a skin tonalities classification. The aim of this paper is to propose a system to skin tonalities through geographic distribution based on clustering algorithms, pattern recognition and fuzzy logic. This distribution gives us the opportunity to classify the skin tonalities. We can study each skin tonality for any applications as medical diagnosis, security. In the first stage, we use the RGB color model to training the system. Then, we tested the system with different color models. We use color model with the best result to propose geographic distribution based skin tonalities. The results show that is possible to generate a skin tonalities classification. The proposed system is using to skin recognition, showing interesting results under controlled and no controlled conditions.
AB - One of the most significant current discussions in Computer Science is the skin recognition. Many papers have studied the skin detection using different techniques, artificial vision, machine learning, deep learning among others. Despite its long success, the skin recognition has several problems in use. However, there has been little discussion about generate a skin tonalities classification. The aim of this paper is to propose a system to skin tonalities through geographic distribution based on clustering algorithms, pattern recognition and fuzzy logic. This distribution gives us the opportunity to classify the skin tonalities. We can study each skin tonality for any applications as medical diagnosis, security. In the first stage, we use the RGB color model to training the system. Then, we tested the system with different color models. We use color model with the best result to propose geographic distribution based skin tonalities. The results show that is possible to generate a skin tonalities classification. The proposed system is using to skin recognition, showing interesting results under controlled and no controlled conditions.
KW - Color model
KW - Fuzzy logic
KW - Geographic distribution
KW - Skin
UR - http://www.scopus.com/inward/record.url?scp=85070730600&partnerID=8YFLogxK
U2 - 10.1007/s12652-019-01400-4
DO - 10.1007/s12652-019-01400-4
M3 - Artículo
SN - 1868-5137
VL - 11
SP - 2859
EP - 2870
JO - Journal of Ambient Intelligence and Humanized Computing
JF - Journal of Ambient Intelligence and Humanized Computing
IS - 7
ER -