Fuzzy clustering for color recognition application to image understanding

Author

Khodja, Lotfi ; Foulloy, Laurent ; BENOIT, Eric

Author_Institution

Lab. d´´Autom. et de Micro-Inf. Ind., Savoie Univ., Chambery, France

Volume

2

fYear

1996

fDate

8-11 Sep 1996

Firstpage

1407

Abstract

Color related information is used for image analysis purposes. The FCM, the fuzzy KNN, and a proposed interpolation method based on the Delaunay triangulation are applied for the segmentation of color images. Clustering by means of triangulations is computed by linearly interpolating the membership functions. The interpolation is obtained by piece-wise approximation over a triangulation of a set of training samples. We intend to implement this new technique in fuzzy sensors performing a symbolic description of measurements. The Delaunay triangulation has proved to be suitable for clustering tasks

Keywords

computational geometry; fuzzy set theory; image classification; image colour analysis; image segmentation; interpolation; mesh generation; Delaunay triangulation; FCM; color recognition; fuzzy KNN; fuzzy clustering; fuzzy sensors; image analysis; image understanding; interpolation method; piece-wise approximation; Clustering algorithms; Image color analysis; Image recognition; Image segmentation; Interpolation; Iterative algorithms; Minimization methods; Nearest neighbor searches; Performance evaluation; Sensor phenomena and characterization;

fLanguage

English

Publisher

ieee

Conference_Titel

Fuzzy Systems, 1996., Proceedings of the Fifth IEEE International Conference on

Conference_Location

New Orleans, LA

Print_ISBN

0-7803-3645-3

Type

conf

DOI

10.1109/FUZZY.1996.552382

Filename

552382