Automatic edge detection by combining kohonen SOM and the canny operator

Authors:
P. Sampaziotis;N. Papamarkos
Affiliations:
Image Processing and Multimedia Laboratory, Department of Electrical & Computer Engineering, Democritus University of Thrace, Xanthi, Greece;Image Processing and Multimedia Laboratory, Department of Electrical & Computer Engineering, Democritus University of Thrace, Xanthi, Greece
Venue:
CIARP'05 Proceedings of the 10th Iberoamerican Congress conference on Progress in Pattern Recognition, Image Analysis and Applications
Year:
2005

Citing 7
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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.