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https://open.uns.ac.rs/handle/123456789/9269
Title: | Selection of optimal features for texture characterization and perception | Authors: | Gebejes A. Huertas R. Tomić, Ivana Stepanic M. |
Issue Date: | 1-Jan-2013 | Journal: | 2013 Colour and Visual Computing Symposium, CVCS 2013 | Abstract: | Different approach to texture characterization can be considered. In this work texture are analyzed through second order statistical measurements based on the Grey-Level Co-occurrence Matrix proposed by Haralick [1]. By this method is possible to compute 22 different features to describe texture. Usually, in previous works, only 5 features are considered among the complete set, but no reasons are exposed for that selection. In this work, using Principal Component Analysis, the set of features is studied and 5 features, different from former, are proposed as the most convenient describing and characterizing the considered textures. Finally, the relationship between the proposed features and perception of texture is analyzed. © 2013 IEEE. | URI: | https://open.uns.ac.rs/handle/123456789/9269 | ISBN: | 9781479906091 | DOI: | 10.1109/CVCS.2013.6626278 |
Appears in Collections: | FTN Publikacije/Publications |
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