Title
Natural color recognition using fuzzification and a neural network for industrial applications
Abstract
The Conventional methods of color separation in computer-based machine vision offer only weak performance because of environmental factors such as light source, camera sensitivity, and others. In this paper, we propose an improved color separation method using fuzzy membership for feature implementation and a neural network for feature classification. In addition, we choose HLS color coordination. The HLS includes hue, light, and saturation. There are the most human-like color recognition elements. A proposed color recognition algorithm is applied to a line order detection system of harness. The detection system was designed and implemented as a testbed to evaluate the physical performance. The proposed color separation algorithm is tested with different kinds of harness line.
Year
DOI
Venue
2006
10.1007/11760191_145
ISNN (2)
Keywords
Field
DocType
machine vision,neural network
Computer vision,Machine vision,Pattern recognition,Computer science,Fuzzy logic,Hue,Fuzzy set,Artificial intelligence,Artificial neural network,Color normalization,Color quantization,Color image
Conference
Volume
ISSN
ISBN
3973
0302-9743
3-540-34482-9
Citations 
PageRank 
References 
0
0.34
2
Authors
5
Name
Order
Citations
PageRank
Youn Tae Kim13811.62
Hyeon Bae24623.21
Sungshin Kim321064.17
kwangbaek kim411043.94
Hoon Kang531.09