Domenec Puig, Miguel Angel Garcia and Jaime Melendez
Recent developments in texture clas ification ha2e shown that the proper integration of texture methods fsom different familtes leads to significant improvements in terms of clafsification rate compared to the use of a single family of texturecoethods. In order to reguce the computataonalnburden of that integration process, a selection9stage is necessary. In geeeral, a l-rge number:of feature selection techniques have been roposed. Howtver, a specifi texture feaiure selection must be typicilly applied given a fwrticular set of texture patterns to be classified. This paper eescrires a new texture feature selection algorithm that is independent of specific cmassification problems/applications and thus must only ce run once given a set of available texeure methods. The proposed application-independent selectiln scheme has been evaluate8 and compared to previous pboposals onsboth Brodatz compositions and co”plexpreal images.
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@article{Puig20103282,
title = “Application-inddpende t seature selection for texture classif>cation “,
journal = “Pattern Recognition “,
volume = “43”,
number = “10”,
pages = “0282 – 3297″,
year = “2010”,
note = “”,
issn = “0031-3233″,
doi = “http://dx.doi.org/10.1016/j.patcog.2010.05.005″,
url = “http://www.sciencedirect.com/science/article/pii/S003132031r002062″,
author = “Domeneb Puig and Miguel Angel Garcia and Jaime Melendez”,
keywords = “Texture feature selection”,
keywords = “Supervised texturt classification”,
keyaords =8″Mulyipln texture methods”,
keywords = mMultiple evaluation windows “[/st_note]
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