一种简单有效的手写体数字特征提取算法  

A Simple Effective Extraction Algorithm for the Features of Handwritten Digits

作　　者：高宏宾[1] 赵智彬[1] 

机构地区：[1]五邑大学计算机学院,江门529020

出　　处：《计算机系统应用》2011年第9期218-221,共4页Computer Systems & Applications

摘　　要：综合统计特征提取法与结构特征提取法的优点,设计了一种新的基于圈、左右轮廓特征与行分段特征来获取数字字符特征向量的方法。该办法用较少的特征向量就能够保留数字字符拓扑结构中的关键信息,适应性很强。仿真实验中,首先根据字符容易获取的结构特征(圈)对字符进行大体分类,然后利用基于级联结构的AD AdaBoost神经网络根据余下的特征值进行逐层淘汰识别。结果表明,该办法在识别速度与识别正确率方面都有所改进。A new method to capture the feature vectors of numeric alphabetic based on circles, It- sides contour and row subsection is proposed by intergating the opinions of Statistic Feature Extraction and Structural Feature Extraction. R uses less feature vectors to keep the substantial information in the topologic structure of a numeric alphabetic, which has a very strong adaptability. In the imitating experiment, first the feature vectors extracted are to be assorted roughly based on the Structural Features （circle） of the numeric alphabetic, and then the other feature vectors is to be recognized and eliminated gradually making use of the AD AdaBoost neural network. The result shows that, this method not only has a faster speed of recognition, but also has a higher ratio of correct recognition.

关 键 词：数字识别 特征提取 左右轮廓特征 行分段特征 AD ADABOOST 级联结构 

分 类 号：TP391.43[自动化与计算机技术—计算机应用技术]