Paper Info
Title
A Facial-Skin Condition Classification System Using Texture and Fuzzy C-Means Technologies
Abstract
This paper describes a facial-skin condition classification system based on cosmeticians' suggestions to let the users realize their facial-skin conditions. Two kinds of features are extracted from the captured skin image. The contrast, inverse difference moment, deviation information in the gray-value histogram, and the entropy of the co-occurrence matrix information are calculated as the firs kind of features. Four parameters in Wavelet domain are used as the second kind of features. A 2-stage fuzzy c-means process is used to classify these 2 kinds of features into 3 groups: the oily skin, neutral skin, and the dry skin. In the two experiments, the classified results are compared with the cosmeticians' results, and the average correct rate is 93%.
Year
DOI
Venue
2007
10.1109/FSKD.2007.22
FSKD (4)
Keywords
Field
DocType
facial-skin condition,fuzzy set theory,inverse difference moment,wavelet transforms,dry skin,matrix algebra,2-stage fuzzy c-means process,gray-value histogram,firs kind,feature extraction,image classification,oily skin,facial-skin condition classification system,skin image,fuzzy c-means technology,wavelet domain,image texture,co-occurrence matrix information,neutral skin,fuzzy c-means technologies,skin,deviation information,classification system,co occurrence matrix
Histogram,Computer science,Fuzzy set,Artificial intelligence,Contextual image classification,Wavelet transform,Wavelet,Computer vision,Pattern recognition,Image texture,Fuzzy logic,Feature extraction,Machine learning
Conference
Volume
ISBN
Citations 
4
978-0-7695-2874-8
0
PageRank 
References 
Authors
0.34
7
4
Name
Order
Citations
PageRank
Jiann-Der Lee121134.02
Yuchi Chen232024.81
Li-Chang Liu3277.58
Chung-Hsien Huang4397.92