Please use this identifier to cite or link to this item:
https://open.uns.ac.rs/handle/123456789/9269
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Gebejes A. | en |
dc.contributor.author | Huertas R. | en |
dc.contributor.author | Tomić, Ivana | en |
dc.contributor.author | Stepanic M. | en |
dc.date.accessioned | 2019-09-30T09:14:44Z | - |
dc.date.available | 2019-09-30T09:14:44Z | - |
dc.date.issued | 2013-01-01 | en |
dc.identifier.isbn | 9781479906091 | en |
dc.identifier.uri | https://open.uns.ac.rs/handle/123456789/9269 | - |
dc.description.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. | en |
dc.relation.ispartof | 2013 Colour and Visual Computing Symposium, CVCS 2013 | en |
dc.title | Selection of optimal features for texture characterization and perception | en |
dc.type | Conference Paper | en |
dc.identifier.doi | 10.1109/CVCS.2013.6626278 | en |
dc.identifier.scopus | 2-s2.0-84889011879 | en |
dc.identifier.url | https://api.elsevier.com/content/abstract/scopus_id/84889011879 | en |
item.grantfulltext | none | - |
item.fulltext | No Fulltext | - |
crisitem.author.dept | Fakultet tehničkih nauka, Departman za grafičko inženjerstvo i dizajn | - |
crisitem.author.parentorg | Fakultet tehničkih nauka | - |
Appears in Collections: | FTN Publikacije/Publications |
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