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Author Levrat, E. ♦ Bombardier, V. ♦ Lamotte, M. ♦ Bremont, J.
Source IEEE Xplore Digital Library
Content type Text
Publisher Institute of Electrical and Electronics Engineers, Inc. (IEEE)
File Format PDF
Copyright Year ©1992
Language English
Subject Domain (in DDC) Computer science, information & general works ♦ Special computer methods
Subject Keyword Image segmentation ♦ Image edge detection ♦ Clustering algorithms
Abstract A segmentation method for gray-level images with fuzzy clustering and local detection of membership variations is presented. The method is very efficient for edge detection in images where transitions between two regions are very large. Two fuzzy operations and a fuzzy c-means algorithm adaptation for pixel clustering are introduced. The influence of the number of clusters on the results is discussed. The results obtained by application of the method to noisy and nonnoisy edges are compared, with those obtained by using the gradient operator.<<ETX>>
Description Author affiliation: Centre de Recherche en Autom., Nancy I Univ., Vandoeuvre, France (Levrat, E.; Bombardier, V.; Lamotte, M.; Bremont, J.)
ISBN 0780302362
Educational Role Student ♦ Teacher
Age Range above 22 year
Educational Use Research ♦ Reading
Education Level UG and PG
Learning Resource Type Article
Publisher Date 1992-03-08
Rights Holder Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Size (in Bytes) 480.75 kB
Page Count 8
Starting Page 221
Ending Page 228


Source: IEEE Xplore Digital Library