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.
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.
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.
Field of Research
080108 Neural, Evolutionary and Fuzzy Computation
Socio Economic Objective
970101 Expanding Knowledge in the Mathematical Sciences
Unless expressly stated otherwise, the copyright for items in DRO is owned by the author, with all rights reserved.
Every reasonable effort has been made to ensure that permission has been obtained for items included in DRO.
If you believe that your rights have been infringed by this repository, please contact email@example.com.
Every reasonable effort has been made to ensure that permission has been obtained for items included in DRO. If you believe that your rights have been infringed by this repository, please contact firstname.lastname@example.org.