Generation of hierarchical dictionary for stroke-order free Kanji handwriting recognition based on substroke HMM
Generation of hierarchical dictionary for stroke-order free Kanji handwriting recognition based on substroke HMM
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基于子笔画隐马尔可夫模型的无笔顺汉字手写识别层次字典的生成
DOI：
10.1109/icdar.2003.1227718
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发表时间：
2003
期刊：
影响因子：
--
通讯作者：
S. Sagayama
中科院分区：
文献类型：
--
作者：
M. Nakai;H. Shimodaira;S. Sagayama
本文提出了一种基于子笔划隐马尔可夫模型（HMM）的汉字层次结构词典的生成方法，用于无笔划数和笔划顺序的手写体识别。在基于笔划的方法中，大量的笔划顺序变化可以通过将不同的笔划序列添加到字典中来容易地表示，并且不需要训练新的参考模式。分层结构字典的优点在于，可以使用定义汉字部分的少量笔画顺序规则来产生汉字字符的数千种笔画顺序变化。此外，识别速度快，因为共同的序列是共享的子笔画网络，即使总数的笔画顺序组合变得巨大的实际。在实验中，使用60名书写者的1016个教育汉字，统计选择了300种不同的汉字部件笔顺规则。通过将这些新的笔画顺序规则添加到字典中，为2965个JIS一级汉字生成了约9000种不同笔画顺序的变体。因此，我们成功地提高了识别准确率从82.6%到90.2%的笔划顺序自由手写。
This paper describes a method of generating a Kanji hierarchical structured dictionary for stroke-number and stroke-order free handwriting recognition based on sub-stroke HMM. In stroke-based methods, a large number of stroke-order variations can be easily expressed by just adding different stroke sequences to the dictionary and it is not necessary to train new reference patterns. The hierarchical structured dictionary has an advantage that thousands of stroke-order variations of Kanji characters can be produced using a small number of stroke-order rules defining Kanji parts. Moreover, the recognition speed is fast since common sequences are shared in a substroke network, even if the total number of stroke-order combinations becomes enormous practically. In experiments, 300 different stroke-order rules of Kanji parts were statistically chosen by using 60 writers' handwritings of 1016 educational Kanji characters. By adding these new stroke-order rules to the dictionary, about 9000 variations of different stroke-orders were generated for 2965 JIS 1st level Kanji characters. As a result, we successfully improved the recognition accuracy from 82.6% to 90.2% for stroke-order free handwritings.