Color segmentation by hierarchical connected components analysis with image enhancement by symmetric neighborhood filters

Author

Westman, Tapani ; Harwood, David ; Laitnen, T. ; Pietikanen, M.

Author_Institution

Dept. of Electr. Eng., Oulu Univ., Finland

Volume

i

fYear

1990

fDate

16-21 Jun 1990

Firstpage

796

Abstract

The authors introduce a general-purpose procedure for image segmentation which combines iterative image enhancement by a symmetric neighborhood filter (SNF) with an iterative, hierarchical connected component (HCC) analysis. Color vector versions of both SNF and HCC are developed, using two common kinds of metrics applied to color vector intensity differences-a simple Euclidean-type metric and a coordinate maximum-type metric. The segmentation procedures are illustrated with three-band color images of indoor and outdoor scenes

Keywords

filtering and prediction theory; iterative methods; pattern recognition; picture processing; Euclidean-type metric; color segmentation; color vector intensity differences; coordinate maximum-type metric; hierarchical connected components analysis; iterative image enhancement; symmetric neighborhood filters; Application software; Filters; Image analysis; Image color analysis; Image enhancement; Image segmentation; Iterative algorithms; Layout; Pixel; Robustness;

fLanguage

English

Publisher

ieee

Conference_Titel

Pattern Recognition, 1990. Proceedings., 10th International Conference on

Conference_Location

Atlantic City, NJ

Print_ISBN

0-8186-2062-5

Type

conf

DOI

10.1109/ICPR.1990.118219

Filename

118219