Rassem, Taha H. and Al-Sewari, Abdul Rahman Ahmed Mohammed and Nasrin, M. Makbol (2017) Texture Image Classification Using Wavelet Completed Local Binary Pattern Descriptor (WCLBP). In: IEEE The 7th Conference On Innovative Computing Technology (INTECH 2017), 15-19 August 2017 , University of Bedfordshire, Luton, UK. pp. 15-20.. ISBN 978-150903988-3 (Unpublished)
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Abstract
In this paper, a new texture descriptor inspired from completed local binary pattern (CLBP) is proposed and investigated for texture image classification task. A waveletCLBP (WCLBP) is proposed by integrating the CLBP with the redundant discrete wavelet transform (RDWT). Firstly, the images are decomposed using RDWT into four sub-bands. Then, the CLBP are extracted from the LL sub-bands coefficients of the image. The RDWT is selected due to its advantages. Unlike the other wavelet transform, the RDWT decompose the images into the same size sub-bands. So, the important textures in the image will be at the same spatial location in each sub-band. As a result, more accurate capturing of the local texture within RDWT domain can be done and the exact measure of local texture can be used. The proposed WCLBP is evaluated for rotation invariant texture classification task. The experimental results using CURTex and OuTex texture databases show that the proposed WCLBP outperformed the CLBP and CLBC descriptors and achieved an impressive classification accuracy.
Item Type: | Conference or Workshop Item (Speech) |
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Additional Information: | Conference Proceeding index by Scopus |
Uncontrolled Keywords: | Bins; Classification (of information); Discrete wavelet transforms; Gears; Image classification; Image compression; Wavelet transforms |
Subjects: | Q Science > QA Mathematics > QA76 Computer software |
Faculty/Division: | Faculty of Computer System And Software Engineering |
Depositing User: | Mrs. Neng Sury Sulaiman |
Date Deposited: | 01 Feb 2018 04:36 |
Last Modified: | 04 Oct 2019 03:00 |
URI: | http://umpir.ump.edu.my/id/eprint/18914 |
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