Title
Improving Texture Pattern Recognition by Integration of Multiple Texture Feature Extraction Methods
Abstract
This paper proposes a pixel-based texture classifier that integrates multiple texture feature extraction methods in order to identify the regions of an input image that belong to a given set of texture patterns. Experimental results with textured images of outdoor scenes show that the proposed technique yields lower classification errors than widely recognized texture classifiers based on specific families of texture methods.
Year
DOI
Venue
2002
10.1109/ICPR.2002.1047782
ICPR (3)
Keywords
Field
DocType
proposed technique yield,multiple texture feature extraction,texture method,lower classification error,pixel-based texture classifier,improving texture pattern recognition,outdoor scene,input image,texture pattern,specific family,image classification,computer science,feature extraction,image segmentation,pixel,image recognition,mathematics,pattern recognition,image texture,computer vision
Computer vision,Texture compression,Pattern recognition,Feature detection (computer vision),Image texture,Feature (computer vision),Computer science,Feature extraction,Artificial intelligence,Pixel,Contextual image classification,Texture filtering
Conference
Volume
ISSN
ISBN
3
1051-4651
0-7695-1695-X
Citations 
PageRank 
References 
6
0.51
10
Authors
2
Name
Order
Citations
PageRank
Miguel Ángel Garcia122024.41
Domènec Puig2847.98