Recognition of Off-line Handwriting System based on Hidden Markov Modeling

摘要：

The recognition of cursive handwriting is still an open problem in the pattern recognition domain. In this paper we present an off-line Arabic handwriting recognition system based on hidden markov model. The system extracts a set of features on binary handwritten images using sliding widow, builds character HMM models and learns word HMM models using embedded training without character pre-segmentation. Moreover this paper study the relationship between frame overlap and number of stats. Experiments that have been implemented on the benchmark IFN7ENIT database show the average recognition rate of this system is 85.43％.

关键词： Optical character recognition Arabic handwriting recognition Hidden markov model Sliding window

作者: Dong Xiang Hu Liu Xianqiao Chen Yanfen Cheng

作者单位: School of Computer Science and Technology,Wuhan University of Technology Wuhan 430063,PR China

会议类型: 国际会议

会议名称: 2011 3rd International Conference on Computer and Network Technology(ICCNT 2011)(2011第三届IEEE计算机与网络技术国际会议)

会议地点: 太原

会议语种:英文

页码: 29-32

在线出版日期: 2011-02-26（万方平台首次上网日期，不代表论文的发表时间）