DocumentCode :
2417687
Title :
Confidence Measure as Fuzzy Measure in Color Edge Detection
Author :
Soria-Frisch, Aureli ; Kassid, Abderrahim
Author_Institution :
Pompeu Fabra Univ., Barcelona
fYear :
0
fDate :
0-0 0
Firstpage :
1105
Lastpage :
1110
Abstract :
A framework for the detection of edges on color edges, which is based on the application of the fuzzy integral, is proposed herein. The framework makes use of the confidence measure of Meer & Georgescu (2002) in order to automate the construction of the fuzzy measure coefficients. The computation of the confidence measure is achieved by applying a competitive learning algorithm on the input images, whereby the adaptability of the mentioned algorithm is increased. This is not the only advance attained herein, since the automation of the fuzzy measure´s construction furthers the application of the fuzzy integral in computer vision. The framework has been applied in the feasibility study of a system for the reconstruction of frescos. The results in this industrial application are shown together with the performance evaluation on some benchmark images.
Keywords :
computer vision; edge detection; fuzzy set theory; image colour analysis; unsupervised learning; color edge detection; competitive learning algorithm; computer vision; fuzzy measure; Application software; Automation; Color; Computer vision; Construction industry; Fuzzy sets; Humans; Image edge detection; Image reconstruction; Image segmentation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Fuzzy Systems, 2006 IEEE International Conference on
Conference_Location :
Vancouver, BC
Print_ISBN :
0-7803-9488-7
Type :
conf
DOI :
10.1109/FUZZY.2006.1681848
Filename :
1681848
Link To Document :
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