Abstract
In this paper a new method for edge detection in grayscale images is presented. It is based on the use of the Kohonen self-organizing map (SOM) neural network combined with the methodology of Canny edge detector. Gradient information obtained from different masks and at different smoothing scales is classified in three classes (Edge, Non Edge and Fuzzy Edge) using an hierarchical Kohonen network. Using the three classes obtained, the final stage of hysterisis thresholding is performed in a fully automatic way. The proposed technique is extensively tested with success.
Chapter PDF
Similar content being viewed by others
Keywords
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
References
Canny, J.: A computational approach to edge detection. IEEE Transactions on pattern analysis and machine intelligence 8(6), 679–698 (1986)
Liang, L.R., Looney, C.G.: Competitive fuzzy edge detection. Applied Soft Computing 3, 123–137 (2003)
Marr, D., Hildreth, E.: Theory of edge detection. In: Proc. Roy. Soc. London B-207, pp. 187–217 (1980)
Kohonen, T.: Self-Organizing Maps, 2nd edn. Springer, Berlin (1997)
Toivanen, P.J., Ansamaki, J., Parkkinen, J.P.S., Mielikainen, J.: Edge detection in multispectral images using the self-organizing map. Pattern Recognition Letters 24, 2987–2994 (2003)
Yitzhaky, Y., Peli, E.: A Method for Objective Edge Detection Evaluation and Detector Parameter Selection. IEEE Transactions on pattern analysis and machine intelligence 25(8), 1027–1033 (2003)
Bowyerm, K., Kranenburg, C.: Edge Detector Evaluation Using Empirical ROC Curves. Computer Vision and Image Understanding 84, 77–103 (2001)
Law, T., Itoh, H., Seki, H.: Image Filtering, Edge Detection and Edge Tracing Using Fuzzy Reasoning. IEEE Transactions on pattern analysis and machine intelligence 18(5), 481–491 (1996)
Pratt, W.K.: Digital Image Processing, 3rd edn. John Wiley & Sons, Inc., Chichester (2001)
Pinho, A.J.: Modeling Non-Linear Edge Detectors Using Artificial Neural Networks. In: Proc. of the 15th Annual Int. Conf. of the IEEE Eng. in Medicine and Biology Soc., San Diego, CA, U.S.A, pp. 306–307 (October 1993)
Weller, S.: Artificial Neural Net Learns the Sobel Operators (and More), Applications of Artificial Neural Networks II. In: SPIE Proceedings Vol SPIE-1469, pp. 69–76 (August 1991)
Bezdek, J.C., Kerr, D.: Training Edge Detecting Neural networks with Model-Based Examples. In: Proc 3rd International Confererence on Fuzzy Systems, FUZZ-IEEE 1994, Orlando, Florida, USA, June 26 - 29, pp. 894–901 (1994)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2005 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Sampaziotis, P., Papamarkos, N. (2005). Automatic Edge Detection by Combining Kohonen SOM and the Canny Operator. In: Sanfeliu, A., Cortés, M.L. (eds) Progress in Pattern Recognition, Image Analysis and Applications. CIARP 2005. Lecture Notes in Computer Science, vol 3773. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11578079_98
Download citation
DOI: https://doi.org/10.1007/11578079_98
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-29850-2
Online ISBN: 978-3-540-32242-9
eBook Packages: Computer ScienceComputer Science (R0)