Edge Enhancement Post-processing Using Hopfield Neural Net

Authors:
Zhaoyu Pian;Liqun Gao;Kun Wang;Li Guo;Jianhua Wu
Affiliations:
College of Information Science & Engineering, Northeastern University, 110004, Shenyang, China;College of Information Science & Engineering, Northeastern University, 110004, Shenyang, China;College of Information Science & Engineering, Northeastern University, 110004, Shenyang, China;College of Information Science & Engineering, Northeastern University, 110004, Shenyang, China;College of Information Science & Engineering, Northeastern University, 110004, Shenyang, China
Venue:
ISNN '07 Proceedings of the 4th international symposium on Neural Networks: Advances in Neural Networks, Part III
Year:
2007

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Abstract

A novel edge enhancement based on Hopfield neural net is presented in this paper, which is a post-processing complement for a pre-existing edge detector. This term is added to the output of the edge detector. Firstly, the energy function which is used to find the final stable edges is provided in the Hopfield neural net, and then, based on the window iteration, it improves the performance of the edge detector by recovering missing edges and eliminating false edges. In experiments conducted on various images, we demonstrate the performance of the algorithm on them.