| 方天红,贾涵,陈庆虎.Gabor特征和字典学习算法在打印文件鉴别中的应用[J].电子测量与仪器学报,2017,31(4):644-650 |
| Gabor特征和字典学习算法在打印文件鉴别中的应用 |
| Application of gabor feature and dictionary learning algorithm in printed document identification |
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| DOI：10.13382/j.jemi.2017.04.022 |
| 中文关键词: 打印文件 字典学习 Gabor特征 稀疏表示 鉴别 |
| 英文关键词:print document dictionary learning Gabor feature sparse representation identification |
| 基金项目:湖北省教育厅项目（B2015033）、湖北工程学院科研项目（201511）、湖北省大学生创新训练项目(201610528004)资助 |
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| Author | Institution |
| Fang Tianhong | 1. School of Physics and Electronicinformation Engineering, Hubei Engineering University, Xiaogan 432000, China; 2. School of Electronic Information, Wuhan University, Wuhan 430072, China |
| Jia Han | School of Physics and Electronicinformation Engineering, Hubei Engineering University, Xiaogan 432000, China |
| Chen Qinghu | School of Electronic Information, Wuhan University, Wuhan 430072, China |
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| 中文摘要: |
| 为了改善计算机打印文件的自动鉴别性能，提出了一种基于Gabor特征和Fisher判别准则核字典学习的激光打印文件鉴别算法。首先提取字符图像的Gabor幅值特征，同时将Gabor数据特征映射到高维核空间进行主成分分析；再将降维的特征作为初始字典，进行基于Fisher判别准则的字典学习；最后利用稀疏表示分类方法进行鉴别。在自建数据库上的实验结果表明Gabor特征在打印文件机源认证中是一种有效的鉴别特征，实验结果还验证了Gabor特征和Fisher判别准则核字典学习算法的有效性，打印文件源打印机正确鉴别率可达95.79%。 |
| 英文摘要: |
| In order to improve the automatic identification performance of laser print documents, a new sparse representation algorithm based on Gabor features and fisher discrimination kernel dictionary learning was proposed for print documents identification. Proposed method first extracted the image Gabor features, and used kernel principal component analysis to reduce the Gabor features dimension. Based on the fisher discrimination criterion, a dictionary learning method whose dictionary atoms were initialized by the reduced Gabor features was performed. Sparse representation based classification was used to the identification of laser print documents. Experimental results on our database show its efficiency and effectiveness with a correct printer identification rate of 95.79%. |
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