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Texture recognition by using GLCM and various aggregation functions

Beliakov, Gleb, James, Simon and Troiano, Luigi 2008, Texture recognition by using GLCM and various aggregation functions, in 2008 IEEE International Conference on Fuzzy Systems : proceedings : FUZZ-IEEE 2008, IEEE, Piscataway, N.J., pp. 1472-1476.

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Title Texture recognition by using GLCM and various aggregation functions
Author(s) Beliakov, Gleb
James, Simon
Troiano, Luigi
Conference name IEEE International Conference on Fuzzy Systems (17th : 2008 : Hong Kong)
Conference location Hong Kong
Conference dates 1-6 June 2008
Title of proceedings 2008 IEEE International Conference on Fuzzy Systems : proceedings : FUZZ-IEEE 2008
Editor(s) Feng, Gary G.
Publication date 2008
Conference series International Conference on Fuzzy Systems
Start page 1472
End page 1476
Publisher IEEE
Place of publication Piscataway, N.J.
Keyword(s) grey systems
image recognition
image texture
matrix algebra
pattern classification
principal component analysis
Summary We discuss the problem of texture recognition based on the grey level co-occurrence matrix (GLCM). We performed a number of numerical experiments to establish whether the accuracy of classification is optimal when GLCM entries are aggregated into standard metrics like contrast, dissimilarity, homogeneity, entropy, etc., and compared these metrics to several alternative aggregation methods.We conclude that k nearest neighbors classification based on raw GLCM entries typically works better than classification based on the standard metrics for noiseless data, that metrics based on principal component analysis inprove classification, and that a simple change from the arithmetic to quadratic mean in calculating the standard metrics also improves classification.
Notes This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder.
ISBN 9781424418190
ISSN 1098-7584
Language eng
Field of Research 080108 Neural, Evolutionary and Fuzzy Computation
Socio Economic Objective 970101 Expanding Knowledge in the Mathematical Sciences
HERDC Research category E1 Full written paper - refereed
ERA Research output type E Conference publication
HERDC collection year 2008
Copyright notice ©2008, IEEE.
Persistent URL http://hdl.handle.net/10536/DRO/DU:30018289

Document type: Conference Paper
Collections: School of Engineering and Information Technology
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