摘要
针对在手写字符识别中 ,因于书写习惯和风格的不同 ,造成字符模式不稳定的问题 ,利用独立分量对信号重建的良好性能 ,采用独立分量分析的方法抽取字符独立特征 ,并建立字符重建模型 ;通过对重建模型的误差分析进行字符识别 ;对美国国家邮政局USPS(USPostalServicedatabase)字库中全部数字字符完整的识别实验 。
To overcome handwritten character pattern's instability caused by different writing styles, a novel approach is proposed in this paper. By the approach, firstly, Independent Component Analysis (ICA) is used to extract character features and reconstruct character models. And character recognition is then conducted based on the error analysis of reconstructed models'. The proposed algorithm is tested on the entire USPS character database, and the experimental results validate the robustness and accuracy of the proposed algorithm.
出处
《计算机辅助设计与图形学学报》
EI
CSCD
北大核心
2005年第3期455-460,共6页
Journal of Computer-Aided Design & Computer Graphics
基金
空军装备部基础研究项目 (4 0 2 0 5 0 10 2 )
中国科学院知识创新工程领域前沿项目 (CXNIGLAS A0 2 0 12 )
关键词
模式识别
手写字符
独立分量分析
重建模型
pattern recognition
handwritten character
independent component analysis
model reconstruction
