作　　者： ; ; ;

机构地区： 电子科技大学中山学院信息工程学院电子信息工程系

出　　处： 《计算机工程与应用》 2009年第4期190-192,210,共4页

摘　　要： 目前已有研究表明,相对于灰度图像,利用图像的彩色信息能改进人脸图像的识别率。但近年来的彩色人脸识别研究较少。提出了一种基于奇异值向量和RBF神经网络的彩色人脸图像识别方法。首先说明了彩色图像的奇异值向量具有代数和几何不变性,再将降维的奇异值向量作为图像的特征,然后应用RBF神经网络进行训练和识别。实验表明该方法的识别率为95%左右,是一种有效的彩色人脸识别方法。 As opposed to gray images,the color information of face images may be applied to improve the face image recognition rate.But only a few methods for color face recognition has been proposed in the recent years.Based on the singular value vector of color face image and RBF neural network,a method for color face recognition is presented.The algebraic and geometric invariance of singular value vector is firstly given,and then singular value vector compressed is extracted as the image feature,then RBF neural network is used to training and recognition.Experiment shows that the recognition rate of the proposed method is about 95% and it is an effective color face recognition method.

关 键 词： 奇异值 径向基函数神经网络 彩色人脸识别

领　　域： [自动化与计算机技术] [自动化与计算机技术]