Local appearance-based face recognition using adaptive directional wavelet transform
The latest research has shown that adaptive directional wavelet transform can constitute edges and textures in images efficiently due to the adaptive directional selectivity. This paper is primarily focused on the application of adaptive directional wavelet transform in conjunction with linear discr...
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| Format: | Article |
| Language: | English |
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Springer
2019-04-01
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| Series: | Journal of King Saud University: Computer and Information Sciences |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S1319157817300046 |
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| author | Mohd. Abdul Muqeet Raghunath S. Holambe |
| author_facet | Mohd. Abdul Muqeet Raghunath S. Holambe |
| author_sort | Mohd. Abdul Muqeet |
| collection | DOAJ |
| description | The latest research has shown that adaptive directional wavelet transform can constitute edges and textures in images efficiently due to the adaptive directional selectivity. This paper is primarily focused on the application of adaptive directional wavelet transform in conjunction with linear discriminant analysis (LDA) for capturing the discriminant directional multiresolution facial features. The intention of this paper is to explore the efficacy of adaptive directional wavelet transform in facial feature extraction and to offer a stepping stone for further research in this direction. The proposed approach is compared with existing subspace and local descriptor feature extraction methods. A performance comparison is also demonstrated with existing non-adaptive multiresolution analysis methods such as discrete wavelet transform (DWT), Gabor wavelet transform (GWT), curvelets, ridgelets, contourlets, and local Gabor binary pattern. Evaluation of the proposed approach on famous databases such as ORL, Essex Grimace, Yale, and Sterling face convinces the effectiveness of the adaptive directional wavelet transform based subspace features. Keywords: Face recognition, Adaptive directional wavelet transform, Linear discriminant analysis, Multiresolution analysis |
| format | Article |
| id | doaj-art-c17c4dbf65bd4aa58a2038af017bb85b |
| institution | Kabale University |
| issn | 1319-1578 |
| language | English |
| publishDate | 2019-04-01 |
| publisher | Springer |
| record_format | Article |
| series | Journal of King Saud University: Computer and Information Sciences |
| spelling | doaj-art-c17c4dbf65bd4aa58a2038af017bb85b2025-08-20T03:48:41ZengSpringerJournal of King Saud University: Computer and Information Sciences1319-15782019-04-0131216117410.1016/j.jksuci.2016.12.008Local appearance-based face recognition using adaptive directional wavelet transformMohd. Abdul Muqeet0Raghunath S. Holambe1Electrical Engineering Department, Muffakham Jah College of Engineering and Technology, Hyderabad (TS), India; Corresponding author.Department of Instrumentation Engineering, SGGS Institute of Engineering and Technology, Nanded (MS), IndiaThe latest research has shown that adaptive directional wavelet transform can constitute edges and textures in images efficiently due to the adaptive directional selectivity. This paper is primarily focused on the application of adaptive directional wavelet transform in conjunction with linear discriminant analysis (LDA) for capturing the discriminant directional multiresolution facial features. The intention of this paper is to explore the efficacy of adaptive directional wavelet transform in facial feature extraction and to offer a stepping stone for further research in this direction. The proposed approach is compared with existing subspace and local descriptor feature extraction methods. A performance comparison is also demonstrated with existing non-adaptive multiresolution analysis methods such as discrete wavelet transform (DWT), Gabor wavelet transform (GWT), curvelets, ridgelets, contourlets, and local Gabor binary pattern. Evaluation of the proposed approach on famous databases such as ORL, Essex Grimace, Yale, and Sterling face convinces the effectiveness of the adaptive directional wavelet transform based subspace features. Keywords: Face recognition, Adaptive directional wavelet transform, Linear discriminant analysis, Multiresolution analysishttp://www.sciencedirect.com/science/article/pii/S1319157817300046 |
| spellingShingle | Mohd. Abdul Muqeet Raghunath S. Holambe Local appearance-based face recognition using adaptive directional wavelet transform Journal of King Saud University: Computer and Information Sciences |
| title | Local appearance-based face recognition using adaptive directional wavelet transform |
| title_full | Local appearance-based face recognition using adaptive directional wavelet transform |
| title_fullStr | Local appearance-based face recognition using adaptive directional wavelet transform |
| title_full_unstemmed | Local appearance-based face recognition using adaptive directional wavelet transform |
| title_short | Local appearance-based face recognition using adaptive directional wavelet transform |
| title_sort | local appearance based face recognition using adaptive directional wavelet transform |
| url | http://www.sciencedirect.com/science/article/pii/S1319157817300046 |
| work_keys_str_mv | AT mohdabdulmuqeet localappearancebasedfacerecognitionusingadaptivedirectionalwavelettransform AT raghunathsholambe localappearancebasedfacerecognitionusingadaptivedirectionalwavelettransform |