%0 Journal Article
%T Arabic Word Recognition by Classifiers and Context
%A Nadir Farah
%A Labiba Souici
%A Mokhtar Sellami
%A <br>Nadir Farah
%A Labiba Souici
%A and Mokhtar Sellami
%J 计算机科学技术学报
%D 2005
%I 
%X Given the number and variety of methods used for handwriting recognition, it has been shown that there is no single method that can be called the "best". In recent years, the combination of different classifiers and the use of contextual information have become major areas of interest in improving recognition results. This paper addresses a case study on the combination of multiple classifiers and the integration of syntactic level information for the recognition of handwritten Arabic literal amounts. To the best of our knowledge, this is the first time either of these methods has been applied to Arabic word recognition. Using three individual classifiers with high level global features, we performed word recognition experiments. A parallel combination method was tested for all possible configuration cases of the three chosen classifiers. A syntactic analyzer makes a final decision on the candidate words generated by the best configuration scheme. The effectiveness of contextual knowledge integration in our application is confirmed by the obtained results.
%K handwriting recognition
%K multiclassifier systems
%K contextual knowledge
%K Arabic literal amounts<br>手稿识别
%K 多分类系统
%K 阿拉伯文字
%K 文字处理
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=F57FEF5FAEE544283F43708D560ABF1B&aid=19D18E35ECC501FD849BAD9C1184BF13&yid=2DD7160C83D0ACED&vid=A04140E723CB732E&iid=38B194292C032A66&sid=EE23223CE4332BD7&eid=FED44C0135DC1D9C&journal_id=1000-9000&journal_name=计算机科学技术学报&referenced_num=0&reference_num=29