中文日期词的分割与识别

非限定性手写汉字串的分割与识别是当前字符识别领域中的一个难点问题.针对手写日期的特点,提出了整词识别和定长汉字串分割识别相结合的组合识别方法.整词识别将字符串作为一个整体进行识别,无需复杂的字符串分割过程.在定长汉字串分割过程中,首先通过识别来预测汉字串的长度,然后通过投影和轮廓分析确定候选分割线,最后通过识别选取最优分割路径.这两种分割识别方法通过规则进行组合,大大提高了系统的性能.在真实票据图像上的实验表明了该方法的有效性,分割识别正确率达到了93.3%.

Segmentation and Recognition of Handwritten Chinese Day String

Segmentation and recognition of off-line handwritten Chinese character string is a difficult task in the research field of character recognition. A standard way for character string recognition is to segment a string into isolate character, then compos their recognition results into words or strings. The purpose of segmentation is to reduce the pattern classes which are to be sent to the recognition engines. However, recognition failure caused by segmentation line missing, non character patterns and unreliable recognition scores. To recognize the Chinese day strings on check images, a rule based method is proposed. It recognizes date strings by combining a holistic method and a segmentation-recognition based method. The holistic method recognizes the whole string as a single character without segmentation. The segmentation- recognition based method first finds as much candidate segmentation lines as possible by projection and structure analysis. Then, it reduces segmentation lines by a predicted string length. Finally, the best recognition result is selected by recognition scores. Experiments have been done on 5569 real life check images collected from Chinese bank. The experiment results demonstrate the efficiency of the proposed method. The string recognition rate has achieved 93.3 % on the 1932 test strings.