Neural network edge detection-successes and failures

A common problem in image processing is the detection of edges in noisy and incomplete images. Conventional edge detection techniques rely on local gradients which are not robust in noise. Variable thresholding can be used to detect changing edge strengths in the image, but these thresholds have to be found. The present work examines the use of various neural network topologies to improve the robustness of the edge detection in noisy and incomplete images. Throughout the paper neural network edge detection is illustrated by the left ventricle boundary extraction problem in echocardiographic images.