基于改进的MDF特征的手写体数字识别  

Handwritten Numeral Recognition Based on Modified MDF

作　　者：周菲菲[1] 龚声蓉[1] 刘纯平[1] 

机构地区：[1]苏州大学计算机科学与技术学院,江苏苏州215006

出　　处：《小型微型计算机系统》2012年第2期303-306,共4页Journal of Chinese Computer Systems

基　　金：2009年江苏省自然科学基金项目(BK2009116)资助;2009年江苏省科技支撑计划(工业)(BK2009604)资助

摘　　要：方向特征是目前手写体识别中最常用和有效的特征之一.为了减少方向值提取过程中带来的误差,对改进的方向特征(MDF)提出了进一步的改进(MMDF),在方向值提取过程中对方向突变条件进行调整,同时引入半方向归一化线段方向并用二维数组来表示方向值.实验证明采用BP神经网络分类器对手写数字进行识别,与MDF相比,MMDF能同时降低拒识率和提高识别精度.Direction feature is the most commen and effective feature extraction technology in handwritten character recogniton. In or- der to reduce errors during direction value extracting, a number of modifications are proposed to the modifed direction feature （ MDF ） ~ In direction feature value extraction process, some adjustment is performed to the conditon of dirction mutation and half dirction is ~troduction to normalized segment. A two-dimensional array is used to represent the direction value instead of the original one-dimen- sional. The modified MDF{ MMDF） is tested in handwritten numeral database using BP neural network-based classifier and compare to the MDF. MMDF outperformed MDF both in rejection rate and recognition accuray.

关 键 词：手写体识别 方向特征 方向值提取 BP神经网络 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]