基于稀疏PCA的多阶次分数阶傅里叶变换域特征人脸识别
鉴于人脸识别面临光照、表情和遮挡等因素的影响,提出了一种在分数阶傅里叶变换域稀疏表示的人脸识别。基于分数阶傅里叶变换对光照、表情的鲁棒性,已在图像处理领域得到应用。FRFT幅度随阶次的变换呈现压缩性,而SPCA提取其主要信息,且分为主要信息域和次要信息域,融合两者的互补信息组成混合幅度特征,然后融合混合幅度特征、实部特征和虚部特征,最后融合不同阶次下FRFT域特征。此外提出基于贪婪算法的分数阶阶次选择算法和基于Fisherfaces的权重方法。ORL和AR人脸数据库上识别率分别达到了96.5%和97.6%,充分证明了该算法对人脸识别的有效性。...
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| Published in | 计算机应用研究 Vol. 33; no. 4; pp. 1253 - 1257 |
|---|---|
| Main Author | |
| Format | Journal Article |
| Language | Chinese |
| Published |
郑州大学 信息工程学院,郑州,450001
2016
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| Subjects | |
| Online Access | Get full text |
| ISSN | 1001-3695 |
| DOI | 10.3969/j.issn.1001-3695.2016.04.065 |
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| Abstract | 鉴于人脸识别面临光照、表情和遮挡等因素的影响,提出了一种在分数阶傅里叶变换域稀疏表示的人脸识别。基于分数阶傅里叶变换对光照、表情的鲁棒性,已在图像处理领域得到应用。FRFT幅度随阶次的变换呈现压缩性,而SPCA提取其主要信息,且分为主要信息域和次要信息域,融合两者的互补信息组成混合幅度特征,然后融合混合幅度特征、实部特征和虚部特征,最后融合不同阶次下FRFT域特征。此外提出基于贪婪算法的分数阶阶次选择算法和基于Fisherfaces的权重方法。ORL和AR人脸数据库上识别率分别达到了96.5%和97.6%,充分证明了该算法对人脸识别的有效性。 |
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| AbstractList | 鉴于人脸识别面临光照、表情和遮挡等因素的影响,提出了一种在分数阶傅里叶变换域稀疏表示的人脸识别。基于分数阶傅里叶变换对光照、表情的鲁棒性,已在图像处理领域得到应用。FRFT幅度随阶次的变换呈现压缩性,而SPCA提取其主要信息,且分为主要信息域和次要信息域,融合两者的互补信息组成混合幅度特征,然后融合混合幅度特征、实部特征和虚部特征,最后融合不同阶次下FRFT域特征。此外提出基于贪婪算法的分数阶阶次选择算法和基于Fisherfaces的权重方法。ORL和AR人脸数据库上识别率分别达到了96.5%和97.6%,充分证明了该算法对人脸识别的有效性。 TP391.41; 鉴于人脸识别面临光照、表情和遮挡等因素的影响，提出了一种在分数阶傅里叶变换域稀疏表示的人脸识别。基于分数阶傅里叶变换对光照、表情的鲁棒性，已在图像处理领域得到应用。FRFT幅度随阶次的变换呈现压缩性，而SPCA提取其主要信息，且分为主要信息域和次要信息域，融合两者的互补信息组成混合幅度特征，然后融合混合幅度特征、实部特征和虚部特征，最后融合不同阶次下FRFT域特征。此外提出基于贪婪算法的分数阶阶次选择算法和基于Fisherfaces的权重方法。ORL和AR人脸数据库上识别率分别达到了96．5％和97.6％，充分证明了该算法对人脸识别的有效性。 |
| Abstract_FL | Face recognition systems suffers from illumination,expression and occlusion and so on.This paper presented a novel discrete fractional Fourier features method based on sparse principal component analysis (SPCA)for face recognition.It used the fractional Fourier transform (FRFT)to image processing with its robust to illumination and expression.Specially,it handled the magnitude of FRFT,whose energy displayed constringent characteristic,by SPCA to further divide into the main energy of magnitude part (MMP)and the remaining energy of magnitude part (RMP),which combined into the hybrid magnitude part (HMP)to fuse complementary features.Then for fractional Fourier features with individual transform order,the hybrid fractio-nal Fourier features (HFFF)formed and consisted of three fractional Fourier features:HMP,real part (RP)and imaginary part (IP).Finally,it fused the HFFF generated using three fractional Fourier features with different transform orders by means of the weighted summation rule-the decision level fusion-to derive the MOFF for face recognition.In addition,it introduced the greedy search to select the transform order of the FRFT.Experimental results of MOFF on the ORL (96.5%)and AR (97.6%)databases verify the effectiveness of the results by using these new modifications. |
| Author | 王亚星 齐林 郭新 陈恩庆 |
| AuthorAffiliation | 郑州大学信息工程学院,郑州450001 |
| AuthorAffiliation_xml | – name: 郑州大学 信息工程学院,郑州,450001 |
| Author_FL | Guo Xin Wang Yaxing Qi Lin Chen Enqing |
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| ClassificationCodes | TP391.41 |
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| Copyright | Copyright © Wanfang Data Co. Ltd. All Rights Reserved. |
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| DocumentTitleAlternate | Fusion of complementary discrete fractional Fourier features extracted through sparse PCA in generalized frequency domains for face recognition |
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| Keywords | 贪婪算法 特征融合 feature fusion 稀疏主成分分析法(SPCA) face recognition greedy search 人脸识别 分数阶傅里叶变换(FRFT) fractional Fourier transforms sparse principal component analysis |
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| Notes | 51-1196/TP Face recognition systems suffers from illumination,expression and occlusion and so on. This paper presented a novel discrete fractional Fourier features method based on sparse principal component analysis（ SPCA） for face recognition. It used the fractional Fourier transform（ FRFT） to image processing with its robust to illumination and expression. Specially,it handled the magnitude of FRFT,whose energy displayed constringent characteristic,by SPCA to further divide into the main energy of magnitude part（ MMP） and the remaining energy of magnitude part（ RMP）,which combined into the hybrid magnitude part（ HMP） to fuse complementary features. Then for fractional Fourier features with individual transform order,the hybrid fractional Fourier features（ HFFF） formed and consisted of three fractional Fourier features： HMP,real part（ RP） and imaginary part（ IP）. Finally,it fused the HFFF generated using three fractional Fourier features with different transform orders by means of the weighted summation rule- |
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| PublicationTitle | 计算机应用研究 |
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| PublicationYear | 2016 |
| Publisher | 郑州大学 信息工程学院,郑州,450001 |
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| Snippet | 鉴于人脸识别面临光照、表情和遮挡等因素的影响,提出了一种在分数阶傅里叶变换域稀疏表示的人脸识别。基于分数阶傅里叶变换对光照、表情的鲁棒性,已在图像处理领域得到应... TP391.41; 鉴于人脸识别面临光照、表情和遮挡等因素的影响，提出了一种在分数阶傅里叶变换域稀疏表示的人脸识别。基于分数阶傅里叶变换对光照、表情的鲁棒性，已在图像处理领... |
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| SubjectTerms | 人脸识别 分数阶傅里叶变换（FRFT） 特征融合 稀疏主成分分析法（SPCA） 贪婪算法 |
| Title | 基于稀疏PCA的多阶次分数阶傅里叶变换域特征人脸识别 |
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