%0 Journal Article
%T Implicit Polynomial Curve Based on BP Neural Network<br>基于BP神经网络的隐式曲线构造方法
%A LI Dao-lun
%A LU De-tang
%A WU Gang
%A <br>李道伦
%A 卢德唐
%A 吴刚
%J 中国图象图形学报
%D 2004
%I 
%X The implicit polynomial curves have a lot of merits, such as the capability to describe irregularly shaped objects, object recognition and insensitivity to noise, and are used widely in CAGD and computer graphics. A new method for closed curve construction is introduced which is based on the combination of BP neural network and principle of implicit curve construction. The algorithm, first constructs the input and output of the BP neural network from the constraint points and changes the implicit function that represents object boundary into explicit function, then uses BP neural network to fit the curve of the explicit function, and finally obtains the fitting curves that represent the object boundary from the simulation surface. The algorithm has more advancements than the method of fitting the curves of explicit functions by BP network, which can not fit the closed curves. It has good numerical stability and robustness in dealing with noisy or missing data. The Experimental results are given to verify the effectiveness of recovering incomplete images and object boundary reconstruction.
%K implicit function curves
%K fitting
%K BP neural network
%K object boundary representation<br>隐式
%K 显式
%K 物体
%K 构造方法
%K 曲线
%K 函数
%K 逼近方法
%K BP神经网络
%K 计算机图形学
%K 图像复原
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=D06194629680C940ACE75262F54B9D85&aid=685EFDDF2AAF0E20&yid=D0E58B75BFD8E51C&vid=9CF7A0430CBB2DFD&iid=9CF7A0430CBB2DFD&sid=DFBBF6D86DD97199&eid=A6B1729CC57A879A&journal_id=1006-8961&journal_name=中国图象图形学报&referenced_num=2&reference_num=11