一种基于仿生识别的脱机手写体汉字识别方法  

Research on Off-line Handwritten Chinese Characters Recognition Based on Biomimetic Recognition

作　　者：王建平[1] 李帷韬[1,2,3] 王金玲[4] 王熹徽[1] 程羽[1] 

机构地区：[1]合肥工业大学电气工程与自动化学院,合肥230009 [2]东北大学流程工业综合自动化教育部重点实验室,沈阳110004 [3]东北大学自动化研究中心,沈阳110004 [4]合肥工业大学计算机与信息学院,合肥230009

出　　处：《模式识别与人工智能》2008年第1期62-71,共10页Pattern Recognition and Artificial Intelligence

摘　　要：运用仿生模式识别方法构建提取基本笔段的神经元序列覆盖手写体汉字图像,分析笔段神经元间的拓扑性质,将手写体汉字图像转化为具有容错表征方式的6种汉字笔划类型组成的几何图形.模仿人类汉字形码输入法.统计具有冗余容错形状的笔划神经元类型、数量、位置、相合和相交点数量,建立手写体汉字特征知识的数据结构表.对SCUT-IRAC手写体汉字库中手写体汉字识别进行仿真实验。结果证明本文方法具有较强的"认知"手写体汉字的能力.In this paper, biomimetic pattern recognition is employed to construct double weighted elliptical neuron sequence which is used to extract basic stroke segments to cover the handwritten Chinese character image. The topological property of the stroke segment neurons is analyzed. An image of handwritten Chinese characters is transformed into geometric figures composed by six styles of Chinese character strokes with fault tolerance. To imitate typing methods of human Chinese characters font code, the style, the number, the position, the number of joint and the crossover of stroke neurons with redundant fault tolerant shapes are counted. Data structures of characteristic knowledge of handwritten Chinese characters are built. Handwritten Chinese characters from SCUTqRAC HCCLIB are tested and the results confirm the proposed method has the ability of cognizing handwritten Chinese characters.

关 键 词：仿生模式识别 神经元序列 特征知识 容错性 

分 类 号：TP391.43[自动化与计算机技术—计算机应用技术]