Face Recognition Method Based on Fuzzy 2DPCA
2DPCA, which is one of the most important face recognition methods, is relatively sensitive to substantial variations in light direction, face pose, and facial expression. In order to improve the recognition performance of the traditional 2DPCA, a new 2DPCA algorithm based on the fuzzy theory is pro...
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| Format: | Article |
| Language: | English |
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Wiley
2014-01-01
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| Series: | Journal of Electrical and Computer Engineering |
| Online Access: | http://dx.doi.org/10.1155/2014/919041 |
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| author | Xiaodong Li |
| author_facet | Xiaodong Li |
| author_sort | Xiaodong Li |
| collection | DOAJ |
| description | 2DPCA, which is one of the most important face recognition methods, is relatively sensitive to substantial variations in light direction, face pose, and facial expression. In order to improve the recognition performance of the traditional 2DPCA, a new 2DPCA algorithm based on the fuzzy theory is proposed in this paper, namely, the fuzzy 2DPCA (F2DPCA). In this method, applying fuzzy K-nearest neighbor (FKNN), the membership degree matrix of the training samples is calculated, which is used to get the fuzzy means of each class. The average of fuzzy means is then incorporated into the definition of the general scatter matrix with anticipation that it can improve classification result. The comprehensive experiments on the ORL, the YALE, and the FERET face database show that the proposed method can improve the classification rates and reduce the sensitivity to variations between face images caused by changes in illumination, face expression, and face pose. |
| format | Article |
| id | doaj-art-b157cfd7706d49eb9e228eff2ce440d4 |
| institution | Kabale University |
| issn | 2090-0147 2090-0155 |
| language | English |
| publishDate | 2014-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Journal of Electrical and Computer Engineering |
| spelling | doaj-art-b157cfd7706d49eb9e228eff2ce440d42025-02-03T06:43:47ZengWileyJournal of Electrical and Computer Engineering2090-01472090-01552014-01-01201410.1155/2014/919041919041Face Recognition Method Based on Fuzzy 2DPCAXiaodong Li0School of Logistics, Linyi University, Linyi 276005, China2DPCA, which is one of the most important face recognition methods, is relatively sensitive to substantial variations in light direction, face pose, and facial expression. In order to improve the recognition performance of the traditional 2DPCA, a new 2DPCA algorithm based on the fuzzy theory is proposed in this paper, namely, the fuzzy 2DPCA (F2DPCA). In this method, applying fuzzy K-nearest neighbor (FKNN), the membership degree matrix of the training samples is calculated, which is used to get the fuzzy means of each class. The average of fuzzy means is then incorporated into the definition of the general scatter matrix with anticipation that it can improve classification result. The comprehensive experiments on the ORL, the YALE, and the FERET face database show that the proposed method can improve the classification rates and reduce the sensitivity to variations between face images caused by changes in illumination, face expression, and face pose.http://dx.doi.org/10.1155/2014/919041 |
| spellingShingle | Xiaodong Li Face Recognition Method Based on Fuzzy 2DPCA Journal of Electrical and Computer Engineering |
| title | Face Recognition Method Based on Fuzzy 2DPCA |
| title_full | Face Recognition Method Based on Fuzzy 2DPCA |
| title_fullStr | Face Recognition Method Based on Fuzzy 2DPCA |
| title_full_unstemmed | Face Recognition Method Based on Fuzzy 2DPCA |
| title_short | Face Recognition Method Based on Fuzzy 2DPCA |
| title_sort | face recognition method based on fuzzy 2dpca |
| url | http://dx.doi.org/10.1155/2014/919041 |
| work_keys_str_mv | AT xiaodongli facerecognitionmethodbasedonfuzzy2dpca |