Paper Info
Title
Detecting texture edges from images
Abstract
Edge detection takes an important place in image processing and pattern recognition. Its objective is to locate prominent edges in an image, and so to separate the components of an image into subsets that may correspond to the physical objects in the scene. In general, this can be achieved by generating an edge map using, for example, edge detection operators or some threshold techniques. In most cases, these methods assume that at the edge the grey level intensity changes in a discontinuous way (usually as a step function). If we need to segment a textural scene by finding the texture boundaries, traditional methods of edge detection are usually not successful since they cannot distinguish between the micro-edges within each texture and the boundaries between different textures. One reason for their failure is their inability to properly characterize a texture. This problem can be solved by combining the traditional edge detection techniques with some efficient textural measures. That is, in the intensity based edge detection operators, grey levels are replaced by textural features. Recently, the texture spectrum method has been proposed for texture characterization. This paper presents an example of the application of the texture spectrum to edge detection. Promising results are obtained when locating texture boundaries of some of Brodatz's natural images.
Year
DOI
Venue
1992
10.1016/0031-3203(92)90076-U
Pattern Recognition
Keywords
Field
DocType
Texture boundary,Texture analysis,Texture spectrum,Edge detection
Computer vision,Texture compression,Pattern recognition,Image texture,Edge detection,Image processing,Operator (computer programming),Artificial intelligence,Mathematics,Texture filtering,Step function
Journal
Volume
Issue
ISSN
25
6
0031-3203
Citations 
PageRank 
References 
5
0.90
5
Authors
2
Name
Order
Citations
PageRank
Dong-Chen He118921.81
Li Wang212016.84