Title :
Edge detection in a lateral inhibition network
Author :
Kristensen, Terje ; Patel, Ruben
Author_Institution :
Departement of Comput. Sci., Bergen Univ. Coll., Norway
fDate :
6/24/1905 12:00:00 AM
Abstract :
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
Keywords :
edge detection; neural nets; Mach bands; contour lines; edge detection; general purpose neural network environment; lateral inhibition neural network; one-dimensional input patterns; Artificial neural networks; Computer science; Detectors; Educational institutions; Electronic mail; Image edge detection; Intelligent networks; Neural networks; Neurons; Object detection;
Conference_Titel :
Neural Networks, 2002. IJCNN '02. Proceedings of the 2002 International Joint Conference on
Conference_Location :
Honolulu, HI
Print_ISBN :
0-7803-7278-6
DOI :
10.1109/IJCNN.2002.1007760