A statistical approach to multi-scale edge detection

Image and Vision Computing

Volumn 21, Issue 1, 2003, Pages 37-48

  Konishi, Scott ^a   Yuille, Alan ^a   Coughlan, James ^a  

^a SMITH KETTLEWELL EYE RESEARCH INSTITUTE   (United States)

Author keywords

Bayesian inference; Edge detection; Empirical evaluation; Multi scale processing

Indexed keywords

IMAGE ANALYSIS; PROBABILITY DISTRIBUTIONS; STATISTICAL METHODS;

MULTI-SCALE PROCESSING;

EDGE DETECTION;

EID: 0037428196     PISSN: 02628856     EISSN: None     Source Type: Journal    
DOI: 10.1016/S0262-8856(02)00131-2     Document Type: Article

References (21)

1. Babaud J., Witkin A.P., Baudin M., Duda R.O. Uniqueness of the Gaussian Kernel for scale-space filtering. PAMI. 8:(1):1986;26-33.
2. K. Bowyer, C. Kranenburg, S. Dougherty. Edge detector evaluation using empirical ROC curves, Proceedings of Computer Vision and Pattern Recognition, CVPR' 99, Fort Collins, Colorado, 1999, pp. 354-359.
3. Burt P.J. Fast filter transforms for image processing. Computer Graphics and Image Processing. 16:1981;20-51.
4. J. Coughlan, D. Snow, C. English, A.L. Yuille, Efficient optimization of a deformable template using dynamic programming, Proceedings Computer Vision and Pattern Recognition, CVPR'98, 1998, pp. 747-752.
5. Cover T.M., Thomas J.A. Elements of Information Theory. 1991;Wiley InterScience Press, New York.
6. Geman D., Jedynak B. An active testing model for tracking roads in satellite images. IEEE Transactions on Pattern Analysis and Machine Intelligence. 18:(1):1996;1-14.
7. Green D.M., Swets J.A. Signal Detection Theory and Psychophysics. second ed. 1988;Peninsula Publishing, Los Altos, CA.
8. D. Kersten, P. Schrater, The tuning of vision to natural contours: straighter is better, The Annual Meeting of the Vision Sciences Society ARVO, 2001.
9. Koenderink J.J. The structure of images. Biological Cybernetics. 50:1984;363-370.
10. S.M. Konishi, A.L. Yuille, J.M. Coughlan, S.C. Zhu, Fundamental bounds on edge detection: an information theoretic evaluation of different edge cues, Proceedings of Computer Vision and Pattern Recognition, CVPR'99, 1999, pp. 573-579.
11. Konishi S.M., Yuille A.L., Coughlan J.M., Zhu S.C. Statistical edge detection: learning and evaluating edge cues. Pattern Analysis and Machine Intelligence. 2003;. in press.
12. S.M. Konishi, PhD Thesis, Department of Biophysics, University of California at Berkeley, 2002.
13. Marr D. Vision. 1982;W.H. Freeman and Company, San Francisco.
14. Nitzberg M., Mumford D., Shiota T. Filtering Segmentation and Depth. 1993;Springer, Berlin.
15. Perona P., Malik J. Scale-space and edge detection using anisotropic diffusion. IEEE Transactions on Pattern Analysis and Machine Intelligence. 12:(7):1990;629-639.
16. Ripley B.D. Pattern Recognition and Neural Networks. 1996;Cambridge University Press, Cambridge.
17. Vapnik V.N. Statistical Learning Theory. 1998;Wiley, New York.
18. A.P. Witkin, Scale-space filtering. Proceedings of Eighth International Joint Conference on Artificial Intelligence, (Karlsruhe, Germany), 1983, pp. 1019-1022.
19. Yuille A.L., Poggio T. Scaling theorems for zero-crossings. IEEE Transactions on Pattern Analysis and Machine Intelligence PAMI. 8:1986;15-25.
20. Yuille A.L., Coughlan J.M. Fundamental limits of Bayesian inference: order parameters and phase transitions for road tracking. Pattern Analysis and Machine Intelligence. PAMI. 22:(2):2000;160-173.
21. Yuille A.L., Coughlan J.M., Wu Y.N., Zhu S.C. Order parameters for minimax entropy distributions: when does high level knowledge help? International Journal of Computer Vision. 41:(1/2):2001;9-33.