TY - GEN
T1 - A scheme to classify skin through geographic distribution of tonalities using fuzzy based classification approach
AU - Hernandez-Matamoros, Andres
AU - Fujita, Hamido
AU - Nakano-Miyatake, Mariko
AU - Perez-Meana, Hector
AU - Escamilla-Hernandez, Enrique
N1 - Publisher Copyright:
© 2019 The authors and IOS Press. All rights reserved.
PY - 2019/8/29
Y1 - 2019/8/29
N2 - The skin recognition is a topic that has been studying since some years ago using machine learning and artificial vision, nowadays this topic has many applications in the medical industry, for example, cancer detection, injuries, mood recognition, telemedicine, among other applications. In this industry, if we can classify the skin tonalities, we able to limit the diseases that attack each type of skin tonality. Many papers have studied skin recognition, where the goal is the recognition of the skin in a picture or video, they need to have a good database and powerful algorithms of machine learning. This paper proposes a system able to segment the skin through the map and the recognition of the skin in an image. The results show that is possible to generate a skin geographic distribution; it gives the opportunity to classify the skin tonalities, for another hand, we tested the proposed system to recognize skin showing interesting results for different tonalities of skin.
AB - The skin recognition is a topic that has been studying since some years ago using machine learning and artificial vision, nowadays this topic has many applications in the medical industry, for example, cancer detection, injuries, mood recognition, telemedicine, among other applications. In this industry, if we can classify the skin tonalities, we able to limit the diseases that attack each type of skin tonality. Many papers have studied skin recognition, where the goal is the recognition of the skin in a picture or video, they need to have a good database and powerful algorithms of machine learning. This paper proposes a system able to segment the skin through the map and the recognition of the skin in an image. The results show that is possible to generate a skin geographic distribution; it gives the opportunity to classify the skin tonalities, for another hand, we tested the proposed system to recognize skin showing interesting results for different tonalities of skin.
KW - Clustering
KW - Fuzzy logic
KW - RGB color model
KW - Skin
UR - http://www.scopus.com/inward/record.url?scp=85082028176&partnerID=8YFLogxK
U2 - 10.3233/FAIA190034
DO - 10.3233/FAIA190034
M3 - Contribución a la conferencia
T3 - Frontiers in Artificial Intelligence and Applications
SP - 3
EP - 10
BT - Advancing Technology Industrialization Through Intelligent Software Methodologies, Tools and Techniques - Proceedings of the 18th International Conference on New Trends in Intelligent Software Methodologies, Tools and Techniques, SoMeT 2019
A2 - Fujita, Hamido
A2 - Selamat, Ali
PB - IOS Press BV
T2 - 18th International Conference on New Trends in Intelligent Software Methodologies, Tools and Techniques, SoMeT 2019
Y2 - 23 September 2019 through 25 September 2019
ER -
