%0 Journal Article
%T Ellipse extracting from weak edges based on GVF model and the least square method<br>基于改进GVF和最小二乘法的弱边界椭圆提取
%A ZHANG Qiang
%A WANG Kun
%A GUO Li
%A GAO Li-qun
%A <br>张强
%A 王坤
%A 郭丽
%A 高力群
%J 计算机应用
%D 2007
%I 
%X A new fast approach which combines improved GVF model with least square method was proposed to extract ellipse by overcoming the influence of noise and weak edges. At first, the image was preprocessed through median filtering and gradient enhancing of weak boundary, and then the priori knowledge of target region intensity was employed to gain Gaussian fuzzy closeness, which combined with pressure force and formed fussy pressure force. Under the effect of GVF field and the new force, inner control points were pushed toward boundary rapidly, points on the boundary almost bore no forces and outer points bore strong repulsive forces which pushed the points back to the boundary. After iterating several times, the control points were fitted as ellipse by least square method, which was sampled to be new initial boundary of the improved GVF model. The shape-constrained curve deformable method was applied to footprint analysis system and extracted ellipse from blur, noise and weak boundary image precisely, while it was difficult for conventional edge detection methods. Simulation results show that the method is rapid and satisfying.
%K active contour
%K GVF model
%K least square method
%K ellipse extracting
%K weak boundary extracting<br>活动轮廓模型
%K GVF模型
%K 最小二乘法
%K 椭圆提取
%K 弱边缘提取
%K 改进
%K 最小
%K 乘法
%K 边界采样
%K 椭圆提取
%K the
%K least
%K square
%K method
%K model
%K based
%K weak
%K 结果
%K 迭代次数
%K 椭圆轮廓
%K 图像
%K 斑点噪声
%K 纹理噪声
%K 存在
%K 难处理
%K 常规方法
%K 分析系统
%K 赤足足迹
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=831E194C147C78FAAFCC50BC7ADD1732&aid=ED83EA5B282940CC1846A9DF39BA0820&yid=A732AF04DDA03BB3&vid=DB817633AA4F79B9&iid=E158A972A605785F&sid=CA0B5EEC0BAD621A&eid=90C2E72D2E105FF5&journal_id=1001-9081&journal_name=计算机应用&referenced_num=0&reference_num=7