Nagabhushan, P. and Guru, D. S. and Shekar, B. H. (2006) (2D)2 FLD: An efficient approach for appearance based object recognition. Neurocomputing, 69 (7). 934 - 940. ISSN 0925-2312
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In this paper, a new technique called 2-directional 2-dimensional Fisher's Linear Discriminant analysis ((2D)2 FLD) is proposed for object/face image representation and recognition. We first argue that the standard 2D-FLD method works in the row direction of images and subsequently we propose an alternate 2D-FLD which works in the column direction of images. To straighten out the problem of massive memory requirements of the 2D-FLD method and as well the alternate 2D-FLD method, we introduce (2D)2 FLD method. The introduced (2D)2 FLD method has the advantage of higher recognition rate, lesser memory requirements and better computing performance than the standard PCA/2D-PCA/2D-FLD method, and the same has been revealed through extensive experimentations conducted on COIL-20 dataset and AT&T face dataset.
| Item Type: | Article |
|---|---|
| Additional Information: | New Issues in Neurocomputing: 13th European Symposium on Artificial Neural Networks |
| Uncontrolled Keywords: | Principal component analysis, Linear discriminant analysis, Appearance based model, Object recognition, Face recognition |
| Subjects: | D Physical Science > Computer Science |
| Divisions: | Department of > Computer Science |
| Depositing User: | LA manjunath user |
| Date Deposited: | 27 Aug 2019 10:41 |
| Last Modified: | 27 Aug 2019 10:41 |
| URI: | http://eprints.uni-mysore.ac.in/id/eprint/7157 |
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