Segment the metallograph images using Gabor filter

Author

Wen, Jiang ; Zhisheng, You ; Hui, Li

Author_Institution

Dept. of Comput. Sci., Sichuan Univ., Chengdu, China

fYear

1994

fDate

13-16 Apr 1994

Firstpage

25

Abstract

We have implemented a texture-based supervised segmentation method to segment a variety of metallograph images which are considered to contain different textured regions. Texture features are computed by using a set of even symmetric Gabor filters which have been successfully used earlier for a variety of texture classification and segmentation tasks. The performance of the proposed method has been shown on a number of test images. These results also demonstrate the ability of our improved approach to separate the untextured regions from the textured regions in the same image

Keywords

filtering and prediction theory; image segmentation; image texture; metallography; two-dimensional digital filters; even symmetric Gabor filters; image segmentation; metallograph images; microstructure; performance; test images; texture classification; texture segmentation; texture-based supervised segmentation; textured regions; two-dimensional Gabor filter; untextured regions; Computer vision; Filtering theory; Gabor filters; Humans; Image analysis; Image segmentation; Image texture analysis; Information filtering; Information filters; Visual system;

fLanguage

English

Publisher

ieee

Conference_Titel

Speech, Image Processing and Neural Networks, 1994. Proceedings, ISSIPNN '94., 1994 International Symposium on

Print_ISBN

0-7803-1865-X

Type

conf

DOI

10.1109/SIPNN.1994.344974

Filename

344974