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• W2412975045 abstract "This paper presents a face recognition system employing eigenface-based approach. The principal objective of this research is to extract feature vectors from images and to reduce the dimension of information. The method is implemented on frontal view facial images of persons to explore a two-dimensional representation of facial images. The system is organized with RMS (Root Mean Square) contrast scaling technique employed for pre-processing the images to adjust with poor lighting conditions. Experiments have been conducted using Carnegie Mellon University database of human faces and University of Essex Computer Vision Research Projects dataset. Experimental results indicate that the proposed eigenface-based approach can classify the faces with accuracy more than 80% in all cases." @default.
• W2412975045 created "2016-06-24" @default.
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• W2412975045 date "2016-01-01" @default.
• W2412975045 modified "2023-10-16" @default.
• W2412975045 title "Towards Face Recognition Using Eigenface" @default.
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• W2412975045 doi "https://doi.org/10.14569/ijacsa.2016.070505" @default.
• W2412975045 hasPublicationYear "2016" @default.
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