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奇异值和RBF神经网络的彩色人脸识别
Color face recognition based on singular values and RBF neural network
【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。
【Abstract】 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.
【Key words】 singular values; Radial Basis Function(RBF) neural network; color face recognition;
- 【文献出处】 计算机工程与应用 ,Computer Engineering and Applications , 编辑部邮箱 ,2009年04期
- 【分类号】TP391.41
- 【被引频次】8
- 【下载频次】252