面向在线阿拉伯字符识别的混合特征提取方法

Houda Nakkach, Soumaya Hichri, Sofiene Haboubi, H. Amiri
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引用次数: 9

摘要

阿拉伯文字符识别领域多年来受到越来越多的关注,在这方面已经发表了大量的研究论文和报告。阿拉伯字符识别有几个主要问题:阿拉伯字符的拼写不同(取决于它们是孤立的,在单词的开头、中间还是结尾),多个字符可以具有相同的主体,但有一个数字和/或不同的变音符号位置。阿拉伯字符的大小可能因作家而异,甚至在同一作家的作品中也会有所不同,等等。本文提出了一种基于全局特征和局部特征的在线手写阿拉伯字符特征提取方法。该系统对不同作者的2000个汉字进行了测试,获得的最佳识别率为92.43%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Hybrid Approach to Features Extraction for Online Arabic Character Recognition
Recognition of Arabic Character field has been gaining more interest for many years, and a large number of research papers and reports have already been published in this area. There are several major issues with Arabic character recognition: Arabic characters are spelled differently (depending on whether they are isolated, at the beginning, in the middle or at the end of the word), multiple characters can have the same body but a number and/or position of various diacritics. The size of the Arabic characters may vary from one writer to another and even within the writing of a single writer, etc. This paper presents a new approach for feature extraction step of online handwritten Arabic character using global and local features. The system was tested with 2000 Characters written by different writers and the best rate of recognition obtained was 92.43%.
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