Please use this identifier to cite or link to this item: https://ktisis.cut.ac.cy/handle/10488/7235
Title: Topologically invariant texture descriptors
Authors: Eichmann, George 
Kasparis, Takis 
Keywords: Image processing;Image analysis;Algorithms;Topology
Category: Electrical Engineering - Electronic Engineering - Information Engineering
Field: Engineering and Technology
Issue Date: Mar-1988
Publisher: Elsevier
Source: Computer Vision, Graphics and Image Processing, 1988, Volume 41, Issue 3, Pages 267-281
Journal: Computer Vision, Graphics and Image Processing 
Abstract: Texture is one of the important image characteristics and is used to identify objects or regions of interest. The problem of texture classification has been widely studied. Texture classification techniques are either statistical or structural. Some statistical texture classification approaches use Fourier power-spectrum features, while others are based on first- and second-order statistics of gray level differences. Periodic textures that consist of mostly straight lines are of particular interest. In this paper, a new structural approach based on the Hough method of line detection is introduced. This classification is based on the relative orientation and location of the lines within the texture. With proper normalization, the classification is independent of geometrical transformations such as rotation, translation, and/or scaling. Experimental results will also be presented.
URI: http://ktisis.cut.ac.cy/handle/10488/7235
ISSN: 0734-189X
DOI: 10.1016/0734-189X(88)90102-8
Rights: © 1988 by Academic Press
Type: Article
Appears in Collections:Άρθρα/Articles

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