| 基于L1范式的分块2DPCA人脸识别方法 |
| |
| 引用本文： | 郑豪.基于L1范式的分块2DPCA人脸识别方法[J].数据采集与处理,2011,26(6). |
| |
| 作者姓名： | 郑豪 |
| |
| 作者单位： | 南京理工大学计算机科学与技术学院,南京,210094;南京晓庄学院数学与信息技术学院,南京,211171 |
| |
| 基金项目： | 国家自然科学基金(60973098)资助项目; 江苏省高校自然科学基金(09KJD520011)资助项目 |
| |
| 摘 要： | 在人脸识别中,增强人脸图像的重构效果和识别方法的鲁棒性一直是其中的技术难点。为了提高识别性能,先对图像矩阵进行分块,同时用一种新的图像信息熵自适应加权模式对人脸不同分块区域赋予不同的权值,然后直接应用L1范式代替L2范式进行图像特征抽取,最后用最近邻分类器进行分类。实验结果表明,新方法在识别性能上优于基于L1范式的2DPCA方法(2DPCA-L1),比2DPCA-L1更具有鲁棒性,显著地提高了有遮挡图像的重构效果。
|
| 关 键 词： | 人脸识别 特征提取 分块 信息熵 |
Method of Face Recognition Based on L1-Norm and Block Two-Dimensional Principal Component Analysis |
| |
| Zheng Hao.Method of Face Recognition Based on L1-Norm and Block Two-Dimensional Principal Component Analysis[J].Journal of Data Acquisition & Processing,2011,26(6). |
| |
| Authors: | Zheng Hao |
| |
| Affiliation: | Zheng Hao1,2(1.School of Computer Science and Technology,Nanjing University of Science and Technology,Nanjing,210094,China,2.School of Mathematics and Information Technology,Nanjing Xiaozhuang University,211171,China) |
| |
| Abstract: | It is a technical difficulty to enhance the reconstruction of face image and the robustness of recognition method.In order to improve recognition performance,the original images are divided into block images in the proposed approach.At the same time a new image entropy model of adaptive weighted is adopted for giving different block regions with different weights.Then L1-norm,instead of L2-norm is applied directly for image feature extraction.Finally,a nearest neighbor classifier is used for classification.... |
| |
| Keywords: | face recognition feature extraction block entropy |
| 本文献已被 CNKI 万方数据 等数据库收录！ |
|
