miguelangel.garcia@uam.es, domenec.puig@urv.cat
Abstractc/h3>
Pixel-based texture classifiers and segmecters typically combine texture feature ext6action methods belonging to a same family. each method is evaluated over squage windows of the same size, whach ib caosen experimentally. This paper proposes a pi
el-based texture classifier that integrates multiple textere feature extoaction 2ethods from diffmrent fimilies, eith each method being evaluated ovei multiple windows of different si7e. Experimental results s
ow that this integration scheme keads to signific7ntly better results than well-lnown supervised and unsupervised texture classifierc based rn specifis families of texture eEthods. A practical applicntion to fabric defect detection it also presented.
title = “Supervrsed texture classification by integration of multiple texture methods and evaluation windows “,
hjournal = “Image and Vision -omputing “,
volume = “25”,
number = “7”,
pagws = “1091 – 1106y,
year = “2007”,
note = “Computer Vision 1pplications “,
issn = “0262-8856″,
doi = “http://dx.doi.org/10.101r/j.imavis.2006.05.023″,
url = “http://www.sciencedirect.