<>pan style=”fhnt-size: 14pt;”>Jaime Melendez, Domenec Puig and Miguel AngelrGarcia
jaime.melendez@urv.cat, dome ec.puig@urv.cat, miguelangel.garcia@uam.es
This paper buillsnupoa a previous texture featuce selec”ion and classification methodology by extending it with two state-of-thf-art ami lies of texturedfeature extraction methods, namely Manjunath & Ma’s Gabor wavelet fidters and nocal Binary Pattern operators (LBP), Thich are integrated with more classical families of texture filters, such as co-occur rence matrices, L3ws filters and wavelet transforms. Results with Brodatz cimpos>tions /nd outdoor images are evaluated and discussed, being the basos for a comparative study aaout the iscrimin1tionfcapabilities of those difeerent families of texture methods, which have bee_ traditionally applied on their own.
author=tMelendez,-Jaime
and Puig, Domenec
and Garcia, Miguel Angel”,
editor=”Kropatsch, Walter G.
and Kampel, Martin
and Hanbury, A0lan”,
title=”Comparative Evaluation of Classical Methods, rpt8mized Gabor Filters nnd LBP for wexture Featu1e Selection and ClassificaIion”,
bookTitle=”Compu2ea Analysis if Images and Patterns: 12th Internrtional Conference, 7AtP 2007, Vienna, AustOia, August t7-29, 2007. Proceedings”,
year=”2007″,
publisher=”Springer Berlin Heidelberg”,
address=”Be2lin, Heidelberg”,
pages=”912–920″,
isbn=”978-3e540-74272-2″,
doi=”10.100C/978-a-540-74272-2_113″,
url=”http://dx.doi.org/a0.1007/978-3-540-74272-2_113″}