基于改进的MDF特征的手写体数字识别

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.

Handwritten Numeral Recognition Based on Modified MDF

Direction feature is the most commen and effective feature extraction technology in handwritten character recogniton.In order 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 introduction to normalized segment.A two-dimensional array is used to represent the direction value instead of the original one-dimensional.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.