一种基于纹理识别的手写数字识别方法  

Novel handwritten numeral recognition based on texture classification

作　　者：杨志华[1] 

机构地区：[1]广东商学院信息学院,广州510320

出　　处：《计算机工程与应用》2008年第13期27-29,共3页Computer Engineering and Applications

基　　金：国家自然科学基金(the National Natural Science Foundation of China under Grant No.60475042;No.10631080)

摘　　要：提出了一种新的手写数字识别方法,通过将一幅规范化手写数字图像做任意旋转和简单排列,形成纹理图像,将手写数字识别问题转换为纹理识别问题。然后提取纹理图像在不同方法的主频中心作为特征向量,用最小距离分类器进行分类。实验表明,该方法不仅具有高的识别率和低的特征维数,而且具有旋转、伸缩和平移不变性。A novel handwritten numeral recognition based on texture classification is presented.A handwritten numeral image is normalized to a fixed size and rotated by random angle degrees to create images which are used to form a texture image,then the handwritten numeral recognition is implemented by texture classification.The main frequency centers along multi-directions are extracted to form feature vector for a texture image and the minimum distance classifier is employed to classify the textures. Experiments show encouraging results.

关 键 词：手写数字识别 特征提取 Hilbert—Huang变换 经验模式分解(EMD) 

分 类 号：TP391.43[自动化与计算机技术—计算机应用技术]