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首页> 外文期刊>IEEE Transactions on Pattern Analysis and Machine Intelligence >A lexicon driven approach to handwritten word recognition for real-time applications
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A lexicon driven approach to handwritten word recognition for real-time applications

机译:词典驱动的实时应用手写单词识别方法

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摘要

A fast method of handwritten word recognition suitable for real time applications is presented in this paper. Preprocessing, segmentation and feature extraction are implemented using a chain code representation of the word contour. Dynamic matching between characters of a lexicon entry and segment(s) of the input word image is used to rank the lexicon entries in order of best match. Variable duration for each character is defined and used during the matching. Experimental results prove that our approach using the variable duration outperforms the method using fixed duration in terms of both accuracy and speed. Speed of the entire recognition process is about 200 msec on a single SPARC-10 platform and the recognition accuracy is 96.8 percent are achieved for lexicon size of 10, on a database of postal words captured at 212 dpi.
机译:本文提出了一种适用于实时应用的快速手写单词识别方法。预处理,分段和特征提取使用单词轮廓的链码表示来实现。词典条目的字符与输入单词图像的段之间的动态匹配用于按最佳匹配的顺序对词典条目进行排名。定义每个字符的持续时间,并在匹配过程中使用。实验结果证明,在准确性和速度方面,使用可变持续时间的方法要优于使用固定持续时间的方法。在以212 dpi捕获的邮政数据库中,在单个SPARC-10平台上,整个识别过程的速度约为200毫秒,对于词典大小为10的词典,识别精度达到96.8%。

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