%0 Journal Article
%T Method for unsupervised text location based on brightness grading and direction density<br>基于亮度分级和方向密度的无监督文本定位
%A LIU Qiong
%A ZHOU Hui-can
%A WANG Yao-nan
%A <br>刘琼
%A 周慧灿
%A 王耀南
%J 计算机应用
%D 2008
%I 
%X A method for unsupervised text location based on brightness grading and direction density was proposed, which was according to the fact that text in scenes generally has strong contrast with local background. Brightness grading was made in R, G, B color layers separately to decrease the complexity of the background. After that, by using the characteristic of obvious directionality of text strokes, a rough text location was carried out according to direction density. And then, precise discrimination was implemented with a SVM multi-class classifier. The mentioned method overcame the difficulty to choose color clustering number in common unsupervised ways, and constrained the types of candidate areas. Hence the difficulty of training SVM classifier was reduced. Those made the new method had higher accuracy and robustness.
%K RGB brightness
%K gradient orientation
%K unsupervised text location
%K Support Vector Machine (SVM) multi-class classifier<br>RGB亮度
%K 梯度方向
%K 无监督文本定位
%K 支持向量机多类分类器
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=831E194C147C78FAAFCC50BC7ADD1732&aid=62C52887DE19B1D7D9B7A48EA9779A08&yid=67289AFF6305E306&vid=D3E34374A0D77D7F&iid=B31275AF3241DB2D&sid=777A6C995272142B&eid=28652329520A4AA7&journal_id=1001-9081&journal_name=计算机应用&referenced_num=0&reference_num=15