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:	1992-12
上傳時間:	2009-12-23 11:34:52 (UTC+0)
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. Read More: http://www.worldscientific.com/doi/abs/10.1142/S0129065792000310
關聯:	Proceedings of 1992 International Computer Symposium, Taichung, Taiwan, Republic of China,
顯示於類別:	[資訊傳播學系] 會議論文

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