An unsupervised segmentation framework for texture image queries

Author

Chen, Shu-Ching ; Shyu, Mei-Ling ; Zhang, Chengcui

Author_Institution

Sch. of Comput. Sci., Florida Int. Univ., Miami, FL, USA

fYear

2001

fDate

6/23/1905 12:00:00 AM

Firstpage

569

Lastpage

573

Abstract

In this paper a novel unsupervised segmentation framework for texture image queries is presented. The proposed framework consists of an unsupervised segmentation method for texture images, and a multi-filter query strategy. By applying the unsupervised segmentation method on each texture image, a set of texture feature parameters for that texture image can be extracted automatically. Based upon these parameters, an effective multi-filter query strategy which allows the users to issue texture-based image queries is developed The test results of the proposed framework on 318 texture images obtained from the MIT VisTex and Brodatz database are presented to show its effectiveness

Keywords

feature extraction; image retrieval; image segmentation; image texture; visual databases; feature parameters; image databases; image segmentation; texture image queries; texture images; unsupervised segmentation; Computer science; Image databases; Image retrieval; Image segmentation; Image texture analysis; Information retrieval; Information systems; Laboratories; Multimedia systems; Spatial databases;

fLanguage

English

Publisher

ieee

Conference_Titel

Computer Software and Applications Conference, 2001. COMPSAC 2001. 25th Annual International

Conference_Location

Chicago, IL

ISSN

0730-3157

Print_ISBN

0-7695-1372-7

Type

conf

DOI

10.1109/CMPSAC.2001.960669

Filename

960669