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http://dx.doi.org/10.5391/JKIIS.2015.25.5.483

A Texture Classification Based on LBP by Using Intensity Differences between Pixels  

Cho, Yong-Hyun (School of Information Technology Engineering, Catholic University of Daegu)
Publication Information
Journal of the Korean Institute of Intelligent Systems / v.25, no.5, 2015 , pp. 483-488 More about this Journal
Abstract
This paper presents a local binary pattern(LBP) for effectively classifying textures, which is based on the multidimensional intensity difference between the adjacent pixels in the block image. The intensity difference by considering the a extent of 4 directional changes(verticality, horizontality, diagonality, inverse diagonality) in brightness between the adjacent pixels is applied to reduce the computation load as a results of decreasing the levels of histogram for classifying textures of image. And the binary patterns that is represented by the relevant intensities within a block image, is also used to effectively classify the textures by accurately reflecting the local attributes. The proposed method has been applied to classify 24 block images from USC Texture Mosaic #2 of 128*128 pixels gray image. The block images are different in size and texture. The experimental results show that the proposed method has a speedy classification and makes a free size block images classify possible. In particular, the proposed method gives better results than the conventional LBP by increasing the range of histogram level reduction as the block size becomes larger.
Keywords
Intensity Difference; Texture Classification; Local Binary Pattern(LBP); Local Attribute; Image Histogram;
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