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Comparison on PCA ICA and LDA in Face Recognition
| Content Provider | CiteSeerX |
|---|---|
| Author | Christry, C. Pavithra, J. Sathya, F. Mahimai |
| Abstract | Face recognition is used in wide range of application. In recent years, face recognition has become one of the most successful applications in image analysis and understanding. Different statistical method and research groups reported a contradictory result when comparing principal component analysis (PCA) algorithm, independent component analysis (ICA) algorithm, and linear discriminant analysis (LDA) algorithm that has been proposed in recent years. The goal of this paper is to compare and analyze the three algorithms and conclude which is best. Feret Dataset is used for consistency. |
| File Format | |
| Access Restriction | Open |
| Subject Keyword | Face Recognition Pca Ica Feret Dataset Contradictory Result Linear Discriminant Analysis Image Analysis Independent Component Analysis Wide Range Successful Application Principal Component Analysis Different Statistical Method Research Group |
| Content Type | Text |
| Resource Type | Article |
