导　　师： 金连文

学科专业： 081001

授予学位： 硕士

作　　者： ;

机构地区： 华南理工大学

摘　　要： 为了在计算机和用户之间建立一种更直观、更自然和友好的信息交互方式,新型的人机交互技术正逐渐成为研究热点,科学工作者进行了人脸表情识别和汉字识别等多方面的研究工作。围绕这一问题,本论文主要对Gabor特征提取、特征降维及分类器设 计、人脸表情识别系统、手写体汉字识别系统四个方面进行了研究。首先,本文研究了Gabor滤波器的特性,Gabor滤波器在空间域可以看作是一个被Gaussian函数调制的正弦平面波,详细分析了正弦平面波和Gaussian函数的属性,介绍了Gabor特征提取方法以及滤波器组的构成。 其次,本文介绍了两种常用的特征降维的方法PCA和LDA,PCA的目的是寻找在最小均方意义下最能够代表原始数据的投影方法,而LDA的目的是寻找在最小均方意义下最能够区分各类数据的投影方法。在此基础上,本章给出了分类器的设计框图,并重点介绍了针对不同距离测度的距离分类器。 然后本文重点研究了人脸表情识别的预处理、特征提取和分类方法,针对传统的Gabor滤波器组存在特征提取时间较长以及特征数据存在冗余性的缺点,本文提出了一种新颖的局部Gabor滤波器组。为了评估该方法的识别性能,提出了一个基于Gabor特征的人脸表情识别系统。该系统首先对经过预处理之后的纯表情图像提取Gabor特征,然后用PCA+LDA方法对采样后的特征进行特征选择,最后采用距离分类方法识别人脸表情。实验表明这种方法无论在计算量还是识别性能上都比传统的Gabor滤波器组更具有优势。该方法的创新之处在于选取局部Gabor滤波器,对于JAFFE人脸表情数据库,最高平均识别率达到了97.33/%,表明其适合于人脸表情图像的分析。 最后比较了手写体汉字识别中多种方向特征和Gabor特征的识别性能,提出了多尺度Gabor特征提取方法能够获得更高的识别性能,� In order to facilitate a more intelligent, natural and friendly mode for communications between computers and human, novel human computer interface has become a very active research area in computer vision and pattern recognition. There are many approaches have been proposed for facial expression analysis, Chinese character recognition and so on. This thesis studies the problems of Gabor feature extraction, feature reduction and classifier, facial expression recognition system, and handwritten Chinese character recognition. Firstly, we studied the properties of the Gabor filter. The 2D Gabor filter can be regarded as a product of an elliptical Gaussian and a complex plane wave, and then we analyzed the properties of the Gaussian function and the complex plane wave in details. The Gabor feature representation and Gabor filter bank are also introduced. Secondly, there are two classical approaches to reduce the excessive dimensionality by combining features. One approach, known as Principal Component Analysis or PCA, seeks a projection that best represents the data in a least-squares sense. Another approach, knows as Fisher Linear Discriminant or LDA, seeks a projection that best separates the data in a lease-squares sense. Based on the methods, we designed the framework of the classifier, and paid more attention to the details of distance classifiers with different distance metric. Thirdly, we focused on the Facial Expression Recognition /(FER/) system, including the preprocessing procedure, feature extraction and classifier. This paper proposes a new local Gabor filter bank to overcome the disadvantage of the traditional Gabor filter bank, which needs a lot of time to extract Gabor feature vectors and the high-dimensional Gabor feature vectors are very redundant. In order to evaluate the performance of local Gabor filter bank, a FER system based on Gabor feature is presented. The FER system extracts Gabor feature of pure facial expression images, then it uses a two-stage method PCA plus LDA to selec

关 键 词： 滤波器 特征提取 主元分析 线性判别分析 人脸表情识别 手写体汉字识别

领　　域： [自动化与计算机技术] [自动化与计算机技术]