无约束手写体支票金额汉字串识别系统

Unconstrained handwritten Chinese string recognition system for the amount on bank checks

针对手写支票金额汉字串分割和识别都十分困难的特点 ,提出了一种基于隐 Markov模型的 ,分割与识别相结合的算法。该算法具有如下的突出优点 :在分割方面 ,将偏旁部首作为分割的基本单位 ,充分考虑无约束手写汉字分割的各种交叠和粘连情况 ,降低了金额汉字串分割的难度 ;在识别方面 ,通过对字符识别结果采用多选 ,利用动态规划算法来对整串字符进行识别 ,提高了汉字串的识别率。作为处理分割困难的汉字串的一种新思路 ,该方法对于其他手写字符识别问题也具有重要的借鉴意义。

The large variations among the handwritten Chinese characters for the amount on bank checks make segmentation and recognition very difficult. However, a new Chinese string recognition method was developed based on the Hidden Markov Model (HMM) which incorporates both segmentation and recognition. In the segmentation, the Chinese character segment was the basic segmentation unit with consideration of the overlap and conglutination in handwritten Chinese character strings. The accuracy of the Chinese string recognition is greatly increased by using multi -selection candidates and dynamic programming to optimize the final recognition result.