DocumentCode :
3072149
Title :
Comparative analysis of texture models for image segmentation
Author :
Murugswari, G. ; Suruliandi, A.
Author_Institution :
Dept. of Comput. Sci. & Eng., M.S. Univ., Tirunelveli, India
fYear :
2011
fDate :
18-19 March 2011
Firstpage :
115
Lastpage :
118
Abstract :
Texture is one of the high level features of images which is used in many applications. The Local Binary Pattern (LBP) is used for detecting uniform patterns. The dominant local binary pattern (DLBP) makes use of minimum set of most frequently occurred patterns. The Local Texture Pattern (LTP) is the gray-scale and rotational invariant texture measure. It is an ongoing research to find the suitable texture model for particular application. In this paper, the performance of three distinct models is evaluated by using these models for image segmentation.
Keywords :
image colour analysis; image segmentation; image texture; dominant local binary pattern; gray scale; image segmentation; local texture pattern; rotational invariant texture measure; texture model; uniform pattern detection; Accuracy; Computational modeling; Histograms; Image segmentation; Image texture; Pixel; Training; DLBP; LBP; LTP; Texture; segmentation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer, Communication and Electrical Technology (ICCCET), 2011 International Conference on
Conference_Location :
Tamilnadu
Print_ISBN :
978-1-4244-9393-7
Type :
conf
DOI :
10.1109/ICCCET.2011.5762450
Filename :
5762450
Link To Document :
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