Edge detection in a lateral inhibition network
Terje Solsvik Kristensen, Rajni V. Patel · 2003
The paper proposes a method for edge detection based upon a lateral inhibition neural network. Two types of one-dimensional input patterns, a bar and Mach bands are studied. The model is then generalised to two dimensions to show how to extract the boundary of a two-dimensional object. Finally, the method is used to extract different contour lines of a real image. All the models have been developed in a general purpose neural network environment and simulated on a PC.