A feed-forward neural network approach to edge detection
نویسنده
چکیده
This paper presents a novel edge detector based on Feed-Forward Neural Networks (FFNNs). The FFNN computing architecture has two stages, which is a feature enhancement stage as well as a structural boundary extraction stage. The first stage is a traditional supervised BP network, and the second one is manually designed without training. Experiments based on both synthetic and natural images show that the FFNN edge detector can produce accurate, continuous, and smooth edge chains.
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