A SIMPLE SCHEME FOR CONTOUR DETECTION
Gopal Datt Joshi, Jayanthi Sivaswamy
2006
Abstract
We present a computationally simple and general purpose scheme for the detection of all salient object contours in real images. The scheme is inspired by the mechanism of surround influence that is exhibited in 80% of neurons in the primary visual cortex of primates. It is based on the observation that the local context of a contour significantly affects the global saliency of the contour. The proposed scheme consists of two steps: first find the edge response at all points in an image using gradient computation and in the second step modulate the edge response at a point by the response in its surround. In this paper, we present the results of implementing this scheme using a Sobel edge operator followed by a mask operation for the surround influence. The proposed scheme has been tested successfully on a large set of images. The performance of the proposed detector compares favourably both computationally and qualitatively, in comparison with another contour detector which is also based on surround influence. Hence, the proposed scheme can serve as a low cost preprocessing step for high level tasks such shape based recognition and image retrieval.
References
- (2003). http://www.cs.rug.nl/~imaging/databases/contour database/contour database.html.
- Baumann, R., van der Zwan, R., and Peterhans, E. (1997). Figure-ground segregation at contours: a neural mechanism in the visual cortex of the alert monkey. In European Journal of Neuroscience.
- (1998). Robust anisotropic diffusion. In IEEE Transaction on Image Processing.
- Canny, J. (1986). A computational approach to edge detection. In IEEE Transactions on Pattern Analysis and Machine Intelligence.
- Cavanaugh, J., Bair, W., and Movshon, J. (2002). Nature and interaction of signals from the receptive field center and surround in macaque v1 neurons. In Journal of Neurophysiology.
- Dobbins, A., Zucker, S. W., and Cynader, M. S. (1987). Endstopped neurons in the visual cortex as a substrate for calculating curvature. In Nature.
- Dubuc, B. and Zucker, S. (2001). Complexity, confusion and perceptual grouping. part ii: mapping complexity. In International Journal on Computer Vision.
- Grigorescu, C., Petkov, N., and Westenberg, M. (2003). Contour detection based on nonclassical receptive field inhibition. In IEEE Transactions on Image Processing.
- Hubel, D. H. and Wiesel, T. N. (1962). Receptive fields, binocular interaction and functional architecture in the cats visual cortex. In Journal of Psychology.
- Knierim, J. and van Essen, D. (1992). Neuronal responses to static texture patterns in area v1 of the alert macaque monkey. In Journal of Neurophysiology.
- Ma, W.-Y. and Manjunath, B. (2000). Edgeflow: A technique for boundary detection and image segmentation. In IEEE Transactions on Image Processing.
- Marr, D. and Hildreth, E. (1980). Theory of edge detection. In Proceedings of the Royal Society.
- Martin, D. R., Fowlkes, C. C., and Malik, J. (2004). Learning to detect natural image boundaries using local brightness, color, and texture cues. In IEEE Transactions on Pattern Analysis and Machine Intelligence.
- Meer, P. and Georgescu, B. (2001). Edge detection with embedded confidence. In IEEE Transactions on Pattern Analysis and Machine Intelligence.
- Morrone, M. C. and Burr, D. C. (1988). Feature detection in human vision: A phase-dependent energy model. In Proceedings of the Royal Society, London Series B.
- Perona, P. and Malik, J. (1990). Scale-space and edge detection using anisotropic diffusion. In IEEE Transactions on Pattern Analysis and Machine Intelligence.
- Series, P., Lorenceau, J., and Fregnac, Y. (2003). The silent surround of v1 receptive fields: theory and experiments. In Journal of Physiology Paris.
- Shin, M. C., Glodgof, D. B., and Bowyer, K. (2001). Comparision of edge detectors using an object recognition task. In Computer Vision and Image Understanding.
- von der Heydt, R., Peterhans, E., and Drsteler, M. R. (1991). Grating cells in monkey visual cortex: coding texture? In Channels in the Visual Nervous System: Neurophysiology, Psychophysics and Models (Blum B, ed).
- Yen, S. and Finkel, L. (1998). Extraction of perceptually salient contours by striate cortical networks. In Vision Research.
Paper Citation
in Harvard Style
Datt Joshi G. and Sivaswamy J. (2006). A SIMPLE SCHEME FOR CONTOUR DETECTION . In Proceedings of the First International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, ISBN 972-8865-40-6, pages 236-242. DOI: 10.5220/0001374702360242
in Bibtex Style
@conference{visapp06,
author={Gopal Datt Joshi and Jayanthi Sivaswamy},
title={A SIMPLE SCHEME FOR CONTOUR DETECTION},
booktitle={Proceedings of the First International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP,},
year={2006},
pages={236-242},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0001374702360242},
isbn={972-8865-40-6},
}
in EndNote Style
TY - CONF
JO - Proceedings of the First International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP,
TI - A SIMPLE SCHEME FOR CONTOUR DETECTION
SN - 972-8865-40-6
AU - Datt Joshi G.
AU - Sivaswamy J.
PY - 2006
SP - 236
EP - 242
DO - 10.5220/0001374702360242