Unsupervised image segmentation based on the anisotropic texture information

Author

Lin, Cong ; Yuheng, Sha ; Biao, Hou ; Licheng, Jiao

Author_Institution

Inst. of Intelligent Inf. Process., Xidian Univ., Xi´an, China

fYear

2004

fDate

18-20 Dec. 2004

Firstpage

124

Lastpage

127

Abstract

Based on the anisotropic characteristic of brushlet, a new feature named directional texture histogram in brushlet domain is presented, which represents the local anisotropic information in image. A novel unsupervised image segmentation method via local directional texture histogram in the brushlet domain is developed. The segmentation results of synthetic mosaics, aerial photo and synthetic aperture radar (SAR) image show that our method represents better performance and its error probability of the synthetic mosaics is lower than the wavelet-based method.

Keywords

error statistics; image representation; image segmentation; image texture; radar imaging; synthetic aperture radar; wavelet transforms; aerial photo; anisotropic texture information; brushlet domain; directional texture histogram; error probability; image representation; local directional texture histogram; synthetic aperture radar image; synthetic mosaic; unsupervised image segmentation method; wavelet-based method; Anisotropic magnetoresistance; Clustering algorithms; Feature extraction; Histograms; Image analysis; Image segmentation; Performance analysis; Signal processing algorithms; Synthetic aperture radar; Wavelet analysis;

fLanguage

English

Publisher

ieee

Conference_Titel

Image and Graphics (ICIG'04), Third International Conference on

Conference_Location

Hong Kong, China

Print_ISBN

0-7695-2244-0

Type

conf

DOI

10.1109/ICIG.2004.144

Filename

1410402