| 基于RBF神经网络的人脸识别研究 |
| |
| 引用本文： | 吴畏,肖南峰.基于RBF神经网络的人脸识别研究[J].南京气象学院学报,2010(4):307-313. |
| |
| 作者姓名： | 吴畏 肖南峰 |
| |
| 作者单位： | 1,华南理工大学计算机科学与工程学院; |
| |
| 基金项目： | 国家自然科学基金与中国民用航空总局联合资助项目(60776816);; 广东省自然科学重点基金(251064101000005) |
| |
| 摘 要： | 针对人脸识别技术中存在的高维问题、小样本问题和非线性问题展开研究.围绕人脸特征提取,采用基于主成分分析和Fisher线性鉴别来克服在人脸识别中的小样本问题,同时将人脸图像从高维空间映射到低维空间从而解决了高维问题;在分类识别方面,采用具有很强的非线性映射功能的RBF神经网络进行模式分类,能够解决人脸识别中的非线性问题.在ORL人脸数据库上进行的仿真实验表明,该方法进行人脸识别具有较高的识别率.
|
| 关 键 词： | 人脸识别 特征提取 主成分分析 Fisher线性鉴别 RBF神经网络 |
Research on face recognition based on RBF neural networks |
| |
| WuWei XiaoNanfeng.Research on face recognition based on RBF neural networks[J].Journal of Nanjing Institute of Meteorology,2010(4):307-313. |
| |
| Authors: | WuWei XiaoNanfeng |
| |
| Affiliation: | 1 School of Computer Science & Engineering; South China University of Technology; Guangzhou 510006; |
| |
| Abstract: | In this paper,feature extraction and recognition of facial images is studied in order to resolve the highdimension problem,small size samples problem and non-linear separable problem that exist in face recognition technology.The proposed feature extract method based on Principal Component Analysis(PCA) and Fisher s Linear Discriminate(FLD) can solve the small size samples problem and the high-dimension problem by mapping the samples from a high-dimension space to a low-dimension Eigen space.In the recogniti... |
| |
| Keywords: | face recognition feature extraction principal component analysis Fisher s linear discriminate RBF neural network |
|
| 点击此处可从《南京气象学院学报》浏览原始摘要信息 |
|
点击此处可从《南京气象学院学报》下载全文 |
