%0 Journal Article
%T Curve representation and matching based on feature points and minimal area<br>基于特征点和最小面积的曲线描述和匹配
%A ZHANG Gui-mei
%A REN Wei
%A XU Fen
%A <br>张桂梅
%A 任伟
%A 徐芬
%J 计算机应用
%D 2009
%I 
%X In order to recognize the curve whose feature points are the same but the curvature between the feature points is different, a new method for representing and recognizing the contour curve was proposed. First, feature points of the contour were extracted for the rough matching; then the sampling points of the sub-curve were obtained based on the precision requirement using the given minimal area threshold. A new recognition vector of sample points was defined, and a novel recognition vector matrix was constructed based on the recognition vector of sample points; last the similarity of the corresponding sub-curves was calculated by comparing the recognition vector matrix. The curve was recognized by recognizing their each sub-curve. The matching method was a process from simple to complex, thus many redundancies calculations were avoided. The experimental results show the proposed algorithm is efficient and feasible.
%K feature point
%K recognition vector
%K recognition vector matrix
%K curve representation<br>特征点
%K 识别向量
%K 识别向量矩阵
%K 曲线描述
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=831E194C147C78FAAFCC50BC7ADD1732&aid=55FEB76DA5DD837B9B6F8568487989AD&yid=DE12191FBD62783C&vid=771469D9D58C34FF&iid=E158A972A605785F&sid=545EC3172B3789BC&eid=ADA74056AD01F4A8&journal_id=1001-9081&journal_name=计算机应用&referenced_num=2&reference_num=7