%0 Journal Article
%T Active Discriminant Function for Handwriting Recognition<br>基于主动判别函数的手写体识别
%A SUN Guang-Ling
%A LIU Jia-Feng
%A TANG Xiang-Long
%A SHI Da-Ming
%A ZHAO Wei
%A <br>孙广玲
%A 刘家锋
%A 唐降龙
%A 石大明
%A 赵巍
%J 软件学报
%D 2005
%I 
%X A novel recognition method called Active Discriminant Function (ADF) for handwriting recognition is presented. First, statistical feature based Active Prototype Model (APM) in the principal subspace is proposed and an optimal APM corresponding to an unknown pattern is obtained. Second, ADF that is a weighted summation of two distances is proposed. One measures the distance between an unknown pattern and the principal subspace; the other measures the distance between an unknown pattern and the minor subspace. Third, as parameters of ADF, constraints for APM are optimized by applying Minimum Classification Error (MCE) criterion. The optimal constraints help to improve recognition accuracy of ADF. Finally, experiments are conducted on handwritten financial Chinese characters used in bank bill, and empirical results demonstrate that ADF is fairly promising for handwriting recognition.
%K handwriting recognition
%K active discriminant function
%K active prototype model
%K principal component analysis
%K minimum classification error criterion<br>手写体识别
%K 主动判别函数
%K 主动原型模板
%K 主成分分析
%K 最小分类错误准则
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=7735F413D429542E610B3D6AC0D5EC59&aid=980206AED8E77237&yid=2DD7160C83D0ACED&vid=7801E6FC5AE9020C&iid=E158A972A605785F&sid=C81D738643975BB0&eid=640CCB6E396307A8&journal_id=1000-9825&journal_name=软件学报&referenced_num=0&reference_num=17