Image segmentation of color image based on region coherency

Author

Ji, S. ; Park, H.W.

Author_Institution

Dept. of Electr. Eng., Korea Adv. Inst. of Sci. & Technol., Taejon, South Korea

Volume

1

fYear

1998

fDate

4-7 Oct 1998

Firstpage

80

Abstract

A two-step image segmentation algorithm is proposed, which is based on region coherency for the segmentation of color image. The first step is the watershed segmentation, and the next one is the region merging using artificial neural networks. Spatially homogeneous regions are obtained by the first step, but the regions are oversegmented. The second step merges the oversegmented regions. The proposed method exploits the luminance and chrominance difference components of the color image to verify region coherency. The YUV color coordinate system is used in this work

Keywords

brightness; image colour analysis; image segmentation; self-organising feature maps; Kohonen self-organising map; YUV color coordinate system; artificial neural networks; chrominance difference; color image; luminance; oversegmented regions; region coherency; region merging; spatially homogeneous regions; two-step image segmentation algorithm; watershed segmentation; Artificial neural networks; Clustering algorithms; Color; Data compression; Gray-scale; Image reconstruction; Image segmentation; MPEG 4 Standard; MPEG 7 Standard; Merging;

fLanguage

English

Publisher

ieee

Conference_Titel

Image Processing, 1998. ICIP 98. Proceedings. 1998 International Conference on

Conference_Location

Chicago, IL

Print_ISBN

0-8186-8821-1

Type

conf

DOI

10.1109/ICIP.1998.723425

Filename

723425