%0 Journal Article
%T Traffic Sign Recognition Based on Two-dimensional Principal Component Analysis<br>基于二维主成分分析的交通标志牌识别
%A TANG Jin
%A LIU Bo
%A CAI Zi-xing
%A XIE Bin
%A <br>唐琎
%A 刘波
%A 蔡自兴
%A 谢斌
%J 计算机科学
%D 2010
%I 
%X This paper proposed a feature extraction method for traffic sign recognition based on Two-Dimensional Principal Component Analysis (2DPCA). A series of experiments were performed on two traffic sign databases with the nearest neighbor classifier and Euler distance. One database is the image library in which images are obtained through a series of simulation transformation after image binarization, While another database is made up of images shot from real scenes through selecting many different location scenes. The method has a good effect on the recognition of the both image databases.
%K Pattern recognition
%K Traffic sign recognition
%K 2DPCA
%K Feature extraction<br>模式识别，交通标志识别，二维主成分分析，特征提取
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=64A12D73428C8B8DBFB978D04DFEB3C1&aid=F1F5682643A440718482E14F0FE289B7&yid=140ECF96957D60B2&vid=42425781F0B1C26E&iid=708DD6B15D2464E8&sid=EBD6B792C9111B87&eid=334C61CAF4C8EF4E&journal_id=1002-137X&journal_name=计算机科学&referenced_num=0&reference_num=0