基于小波和矩的图像字符特征提取方法研究  

Image Character Feature Extraction Based on Wavelet and Moments Analysis

作　　者：王建平[1] 姜滔[1] 王金玲[1] 朱程辉[1] 王熹徽[1] 

机构地区：[1]合肥工业大学,合肥230009

出　　处：《微电子学与计算机》2003年第11期37-41,共5页Microelectronics & Computer

摘　　要：提取稳定而有代表性的特征是视频图像字符识别的核心问题之一。文章提出了一种基于小波和矩的图像字符特征向量提取方法。通过对字符图像的不同小波分解子图求取不同的矩特征,构造出字符的特征向量。该方法将小波对图像结构精细特征的把握能力强的优点与矩所具有的平移,缩放和旋转不变及抗噪性强的特性有机地结合起来,特征向量稳定、识别准确率高、算法快、抗噪性能强,且特征提取方法具有类人视觉特点。Extracting stabilized and representative feature is the key to character recognition of video image . In this paper , a method of video image character feature extraction is presented based on wavelet and moment analysis . Though seek different moment characters get by the wavelet decomposed sub-graph which got by character image wavelet analysis, to construct character eigenvector. Besides having the invariability to the translation ,scaling and rotation ,this feature vector has the multire solution properties .so it is suitable for classing the very similar objects. Comparing with geometrical moment, the classification rate, recognizing efficiency and antinoise capability of this method have been improved. Furthermore, this feature extraction method has the pattern of human vision.

关 键 词：图像字符 字符特征提取 小波变换 矩特征向量 视频图像 模式识别 小波基函数 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术]