Color Face Recognition Based on Steerable Pyramid Transform and Extreme Learning Machines
This paper presents a novel color face recognition algorithm by means of fusing color and local information. The proposed algorithm fuses the multiple features derived from different color spaces. Multiorientation and multiscale information relating to the color face features are extracted by applyi...
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| Format: | Article |
| Language: | English |
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Wiley
2014-01-01
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| Series: | The Scientific World Journal |
| Online Access: | http://dx.doi.org/10.1155/2014/628494 |
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| _version_ | 1832549627693367296 |
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| author | Ayşegül Uçar |
| author_facet | Ayşegül Uçar |
| author_sort | Ayşegül Uçar |
| collection | DOAJ |
| description | This paper presents a novel color face recognition algorithm by means of fusing color and local information. The proposed algorithm fuses the multiple features derived from different color spaces. Multiorientation and multiscale information relating to the color face features are extracted by applying Steerable Pyramid Transform (SPT) to the local face regions. In this paper, the new three hybrid color spaces, YSCr, ZnSCr, and BnSCr, are firstly constructed using the Cb and Cr component images of the YCbCr color space, the S color component of the HSV color spaces, and the Zn and Bn color components of the normalized XYZ color space. Secondly, the color component face images are partitioned into the local patches. Thirdly, SPT is applied to local face regions and some statistical features are extracted. Fourthly, all features are fused according to decision fusion frame and the combinations of Extreme Learning Machines classifiers are applied to achieve color face recognition with fast and high correctness. The experiments show that the proposed Local Color Steerable Pyramid Transform (LCSPT) face recognition algorithm improves seriously face recognition performance by using the new color spaces compared to the conventional and some hybrid ones. Furthermore, it achieves faster recognition compared with state-of-the-art studies. |
| format | Article |
| id | doaj-art-06c2471c99784011857c24dbcfda8798 |
| institution | Kabale University |
| issn | 2356-6140 1537-744X |
| language | English |
| publishDate | 2014-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | The Scientific World Journal |
| spelling | doaj-art-06c2471c99784011857c24dbcfda87982025-02-03T06:10:49ZengWileyThe Scientific World Journal2356-61401537-744X2014-01-01201410.1155/2014/628494628494Color Face Recognition Based on Steerable Pyramid Transform and Extreme Learning MachinesAyşegül Uçar0Mechatronics Engineering Department, Engineering Faculty, Firat University, 23119 Elazig, TurkeyThis paper presents a novel color face recognition algorithm by means of fusing color and local information. The proposed algorithm fuses the multiple features derived from different color spaces. Multiorientation and multiscale information relating to the color face features are extracted by applying Steerable Pyramid Transform (SPT) to the local face regions. In this paper, the new three hybrid color spaces, YSCr, ZnSCr, and BnSCr, are firstly constructed using the Cb and Cr component images of the YCbCr color space, the S color component of the HSV color spaces, and the Zn and Bn color components of the normalized XYZ color space. Secondly, the color component face images are partitioned into the local patches. Thirdly, SPT is applied to local face regions and some statistical features are extracted. Fourthly, all features are fused according to decision fusion frame and the combinations of Extreme Learning Machines classifiers are applied to achieve color face recognition with fast and high correctness. The experiments show that the proposed Local Color Steerable Pyramid Transform (LCSPT) face recognition algorithm improves seriously face recognition performance by using the new color spaces compared to the conventional and some hybrid ones. Furthermore, it achieves faster recognition compared with state-of-the-art studies.http://dx.doi.org/10.1155/2014/628494 |
| spellingShingle | Ayşegül Uçar Color Face Recognition Based on Steerable Pyramid Transform and Extreme Learning Machines The Scientific World Journal |
| title | Color Face Recognition Based on Steerable Pyramid Transform and Extreme Learning Machines |
| title_full | Color Face Recognition Based on Steerable Pyramid Transform and Extreme Learning Machines |
| title_fullStr | Color Face Recognition Based on Steerable Pyramid Transform and Extreme Learning Machines |
| title_full_unstemmed | Color Face Recognition Based on Steerable Pyramid Transform and Extreme Learning Machines |
| title_short | Color Face Recognition Based on Steerable Pyramid Transform and Extreme Learning Machines |
| title_sort | color face recognition based on steerable pyramid transform and extreme learning machines |
| url | http://dx.doi.org/10.1155/2014/628494 |
| work_keys_str_mv | AT aysegulucar colorfacerecognitionbasedonsteerablepyramidtransformandextremelearningmachines |