Color edge detection with the compass operator
Publication
, Journal Article
Ruzon, MA; Tomasi, C
Published in: Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
January 1, 1999
The compass operator detects step edges without assuming that the regions on either side have constant color. Using distributions of pixel colors rather than the mean, the operator finds the orientation of a diameter that maximizes the difference between two halves of a circular window. Junctions can also be detected by exploiting their lack of bilateral symmetry. This approach is superior to a multidimensional gradient method in situations that often result in false negatives, and it localizes edges better as scale increases.
Duke Scholars
Published In
Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
ISSN
1063-6919
Publication Date
January 1, 1999
Volume
2
Start / End Page
160 / 166
Citation
APA
Chicago
ICMJE
MLA
NLM
Ruzon, M. A., & Tomasi, C. (1999). Color edge detection with the compass operator. Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2, 160–166.
Ruzon, M. A., and C. Tomasi. “Color edge detection with the compass operator.” Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition 2 (January 1, 1999): 160–66.
Ruzon MA, Tomasi C. Color edge detection with the compass operator. Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition. 1999 Jan 1;2:160–6.
Ruzon, M. A., and C. Tomasi. “Color edge detection with the compass operator.” Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, vol. 2, Jan. 1999, pp. 160–66.
Ruzon MA, Tomasi C. Color edge detection with the compass operator. Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition. 1999 Jan 1;2:160–166.
Published In
Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
ISSN
1063-6919
Publication Date
January 1, 1999
Volume
2
Start / End Page
160 / 166