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Optimum Gabor filter design and local binary patterns for texture segmentation
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Li, Ma and Staunton, Richard C. (2008) Optimum Gabor filter design and local binary patterns for texture segmentation. Pattern Recognition Letters, Vol.29 (No.5). pp. 664-672. doi:10.1016/j.patrec.2007.12.001 ISSN 0167-8655.
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WRAP_Staunton_091211-listaunton_prl_paper.pdf - Accepted Version - Requires a PDF viewer. Download (479Kb) |
Official URL: http://dx.doi.org/10.1016/j.patrec.2007.12.001
Abstract
We present a novel approach to multi-texture image segmentation based on the formation of an effective texture feature vector. Texture sub-features are derived from the output of an optimized Gabor filter. The filter's parameters are selected by an immune genetic algorithm, which aims at maximizing the discrimination between the multi-textured regions. Next the texture features are integrated with a local binary pattern, to form an effective texture descriptor with low computational cost, which overcomes the weakness of the single frequency output component of the filter. Finally, a K-nearest neighbor classifier is used to effect the multi-texture segmentation. The integration of the optimum Gabor filter and local binary pattern methods provide a novel solution to the task. Experimental results demonstrate the effectiveness of the proposed approach.
Item Type: | Journal Article | ||||
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Subjects: | Q Science > QA Mathematics > QA76 Electronic computers. Computer science. Computer software | ||||
Divisions: | Faculty of Science, Engineering and Medicine > Engineering > Engineering | ||||
Library of Congress Subject Headings (LCSH): | Texture mapping, Gabor transforms, Image processing -- Digital techniques | ||||
Journal or Publication Title: | Pattern Recognition Letters | ||||
Publisher: | Elsevier BV * North Holland | ||||
ISSN: | 0167-8655 | ||||
Official Date: | 1 April 2008 | ||||
Dates: |
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Volume: | Vol.29 | ||||
Number: | No.5 | ||||
Number of Pages: | 9 | ||||
Page Range: | pp. 664-672 | ||||
DOI: | 10.1016/j.patrec.2007.12.001 | ||||
Status: | Peer Reviewed | ||||
Publication Status: | Published | ||||
Access rights to Published version: | Restricted or Subscription Access | ||||
Date of first compliant deposit: | 14 December 2015 | ||||
Date of first compliant Open Access: | 14 December 2015 |
Data sourced from Thomson Reuters' Web of Knowledge
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