DocumentCode :
2749706
Title :
A Texture Extraction Method Based on Local Binary Pattern Operator
Author :
San, Xing ; Tian, Xinmei ; Wu, Xiuqing
Author_Institution :
Dept. of Electron. Eng. & Inf. Sci., Univ. of Sci. & Technol. of China, Hefei
Volume :
2
fYear :
0
fDate :
0-0 0
Firstpage :
10092
Lastpage :
10095
Abstract :
Most of image texture extraction methods are of high computational complexity, which hardly restricts their application in image processing fields. This paper proposes an improved local binary pattern operator to extract the image texture features. In the algorithm, single pixel is replaced with homogeneous object obtained by an object-oriented image segmentation method to exact image texture. At the same time, conditional probability is adopted as the parameter of image texture. The improvement makes it more valid to analysis object by fuzzy inference based image textures. In our experiments, the extracted image texture features are utilized for classifying images. The achieved good results indicate that the proposed method is faster than other methods while remaining close classification performance
Keywords :
feature extraction; fuzzy reasoning; image classification; image segmentation; image texture; probability; binary pattern operator; conditional probability; fuzzy inference; image classification; image texture feature extraction; object-oriented image segmentation; Computational complexity; Data mining; Image analysis; Image processing; Image segmentation; Image texture; Image texture analysis; Inference algorithms; Information science; Pixel; classification; image texture; local binary pattern; support vector machines;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Control and Automation, 2006. WCICA 2006. The Sixth World Congress on
Conference_Location :
Dalian
Print_ISBN :
1-4244-0332-4
Type :
conf
DOI :
10.1109/WCICA.2006.1713974
Filename :
1713974
Link To Document :
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