Texture Segmentation Based on Probabilistic Index Maps

Author

Dong, Junyu ; Hu, Xiaoming ; Dong, Xinghui ; Wu, Jiahua ; Zou, Ping

Author_Institution

Dept. of Comput. Sci., Ocean Univ. of China, Qingdao, China

fYear

2009

fDate

17-20 April 2009

Firstpage

35

Lastpage

39

Abstract

The Probabilistic Index Map (PIM) model was originally proposed for video processing to extract background of video frames. In this paper, we introduce the PIM model for texture segmentation. We first extract texture features based on Laws and Gabor filters respectively. Then we present a fuzzy k-means method to generate the index map and palette, and use the PIM model to improve the segmentation accuracy. Based on the comparison of experimental results produced using different features and different resolutions, we show the proposed method is effective for texture segmentation.

Keywords

Gabor filters; feature extraction; fuzzy set theory; image colour analysis; image segmentation; image texture; pattern clustering; probability; video signal processing; Gabor filter; PIM model; fuzzy k-mean clustering method; palette; probabilistic index map; texture feature extraction; texture segmentation; video processing; Biomedical imaging; Data mining; Image segmentation; Image texture analysis; Pixel; Probability distribution; Rough surfaces; Sea surface; Shape; Surface texture; Fuzzy K-Means; Gabor; Laws; PIM model; texture segmentation;

fLanguage

English

Publisher

ieee

Conference_Titel

Education Technology and Computer, 2009. ICETC '09. International Conference on

Conference_Location

Singapore

Print_ISBN

978-0-7695-3609-5

Type

conf

DOI

10.1109/ICETC.2009.41

Filename

5169448