A robust two-stage system for image segmentation

Author

López-Rubio, Ezequiel ; Muñoz-Pérez, José ; Gómez-Ruiz, José Antonio

Author_Institution

ETSI Inf., Malaga Univ., Spain

Volume

1

fYear

2000

fDate

2000

Firstpage

606

Abstract

This paper proposes a new method to split images into regions. It consists of two subsystems: cluster detection and cluster fusion. The cluster detection is performed by a competitive neural network or the k-means algorithm, followed by an algorithm which obtains connected clusters. The cluster fusion involves a procedure that is based on the theory of equivalence relations. Proofs are given for the significant properties that we have found. It is not necessary to specify the number of regions in advance, which is a significant improvement over the standard competitive-style strategies. Finally, simulation results are given to demonstrate the performance of this method for some images

Keywords

image segmentation; pattern clustering; cluster detection; cluster fusion; competitive neural network; equivalence relations; image regions; image segmentation; image splitting; k-means algorithm; robust two-stage system; Clustering algorithms; Clustering methods; Computer vision; Gaussian distribution; Gaussian processes; Image segmentation; Neural networks; Partitioning algorithms; Pixel; Robustness;

fLanguage

English

Publisher

ieee

Conference_Titel

Pattern Recognition, 2000. Proceedings. 15th International Conference on

Conference_Location

Barcelona

ISSN

1051-4651

Print_ISBN

0-7695-0750-6

Type

conf

DOI

10.1109/ICPR.2000.905410

Filename

905410