DocumentCode
1742376
Title
Graph-based features for texture discrimination
Author
Grigorescu, C. ; Petkov, Nicolai
Author_Institution
Dept. of Comput. Sci., Groningen Univ.
Volume
3
fYear
2000
fDate
2000
Firstpage
1076
Abstract
Graph-based features, such as the number of connected components, edges of a given orientation and vertices per unit area, and the number of vertices and pixels per connected component, are proposed for the analysis of textures which consist of structural elements. The proposed set of features is compared with features obtained by a typical filter-based scheme which makes use of Gabor filters. The discrimination properties of the two types of features are assessed by evaluating the separability of sets of feature vectors which are derived from different types of texture using the Mahalanobis distance. The graph-based features are shown to be superior to the filter-based features for the class of concerned textures. They are particularly suited for discrimination between textures which have the same spatial and orientation regularity but consist of elements of different forms
Keywords
feature extraction; filtering theory; graph theory; image representation; image texture; Gabor filters; Mahalanobis distance; feature extraction; graph representation; graph-based features; image texture; texture discrimination; Feature extraction; Gabor filters; Maximum likelihood detection; Nonlinear filters; Pixel; Statistics;
fLanguage
English
Publisher
ieee
Conference_Titel
Pattern Recognition, 2000. Proceedings. 15th International Conference on
Conference_Location
Barcelona
ISSN
1051-4651
Print_ISBN
0-7695-0750-6
Type
conf
DOI
10.1109/ICPR.2000.903732
Filename
903732
Link To Document