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A single-layer neural network for parallel thinning

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題名: A single-layer neural network for parallel thinning 作者: R. Y. Wu;W. H. Tsai

貢獻者: Department of Information Communication 日期: 1992

上傳時間: 2009-11-25T02:31:00Z 出版者: Asia University

摘要: A single-layer recurrent neural network is proposed to perform thinning of binary images. This network iteratively removes the contour points of an object shape by template matching. The set of templates is specially designed for a one-pass parallel thinning algorithm. The proposed neural network produce the same results as the algorithm. Neurons in the neural network performs a sigma-pi function to collect inputs. To obtain this function, the templates used in the algorithm are transformed to equivalent Boolean expressions. After the neural network

converges, a perfectly 8-connected skeleton is derived. Good experimental results show the feasibility of the proposed approach.

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