NDLI: Texture description and recognition using combined feature sets

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2010 2nd International Conference on Computer Engineering and Technology

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Volume 2 - 2010

Volume 1 - 2010

2009 International Conference on Computer Engineering and Technology

Texture description and recognition using combined feature sets

Content Provider	IEEE Xplore Digital Library
Author	Jing Liu Jiyin Sun Shan Chen Junlin Zhu
Copyright Year	2010
Description	Author affiliation: Xi'an Research Institute of High-tech, Shanxi, China (Jing Liu; Jiyin Sun; Shan Chen; Junlin Zhu)
Abstract	The nonsubsampled contourlet transform (NSCT) overcomes the aliasing phenomenon of contourlet transform, and has better direction selectivity and translation-invariant than the contourlet transform which is essential for texture analysis. So according to the directional property and coefficients energy feature in NSCT decomposition, we proposed a new algorithm which combined NSCT with LBP. First, aligned two texture image through estimate the texture direction by Radon transform. Then, NSCT features are extracted from NSCT coefficients of images and LBP features is extracted in low frequency to realize the characteristic of multi-scale. Finally two features combined into a new feature named NSCT-LBP according to the different weight and we defined a new similarity measure for recognition. The algorithm is tested on texture images from Brodatz album and KTH-TIPS data set. Experimental results demonstrate that the proposed method produces more accurate recognition results than other well-known methods and overcome the deficiency of original algorithms in rotation and scale transform, and more robust to texture recognition.
File Size	1056599
File Format	PDF
ISBN	9781424463473
e-ISBN	9781424463497
DOI	10.1109/ICCET.2010.5485884
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-04-16
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Wavelet transforms Target recognition Image processing Radon Transform Data mining Image texture analysis Sun target recognition NSCT Frequency Feature extraction Filter bank Robustness LBP texture image
Content Type	Text
Resource Type	Article

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