Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
10361227 | Pattern Recognition | 2005 | 4 Pages |
Abstract
In this study, the edge detection task in vector-valued images is examined as a clustering problem. Using samples within a data window, the minimal spanning tree (MST) provides the ordering of multivariate observations and facilitates the identification of similar classes. The edge detector parameters like edge strength, type and orientation are subsequently determined from the clustered data. Experiments and comparisons are performed, revealing the enhanced performance of the proposed approach.
Related Topics
Physical Sciences and Engineering
Computer Science
Computer Vision and Pattern Recognition
Authors
Ch. Theoharatos, G. Economou, S. Fotopoulos,