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