Lorigo Liana M, Govindaraju Venu
Department of Computer Science and Engineering, State University of New York at Buffalo, Amherst 14228, USA.
IEEE Trans Pattern Anal Mach Intell. 2006 May;28(5):712-24. doi: 10.1109/TPAMI.2006.102.
The automatic recognition of text on scanned images has enabled many applications such as searching for words in large volumes of documents, automatic sorting of postal mail, and convenient editing of previously printed documents. The domain of handwriting in the Arabic script presents unique technical challenges and has been addressed more recently than other domains. Many different methods have been proposed and applied to various types of images. This paper provides a comprehensive review of these methods. It is the first survey to focus on Arabic handwriting recognition and the first Arabic character recognition survey to provide recognition rates and descriptions of test data for the approaches discussed. It includes background on the field, discussion of the methods, and future research directions.
扫描图像上文本的自动识别催生了许多应用，如在大量文档中搜索单词、自动分拣邮政信件以及方便地编辑先前打印的文档。阿拉伯文字手写领域存在独特的技术挑战，并且相较于其他领域，其得到关注的时间较晚。人们已经提出了许多不同的方法并将其应用于各种类型的图像。本文对这些方法进行了全面综述。这是第一篇专注于阿拉伯手写体识别的综述，也是第一篇提供所讨论方法的识别率和测试数据描述的阿拉伯字符识别综述。它包括该领域的背景、方法讨论以及未来研究方向。
