Face recognition for remote database backup system
Face recognition is one of the most interesting applications in the image processing field.To build a model to recognize the face of different people, we need to do several processes on the image to obtain the most efficient features.In this research a face recognition model is developed.The dataset...
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Main Authors: | , , , , |
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Format: | Conference or Workshop Item |
Language: | English |
Published: |
2011
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Subjects: | |
Online Access: | http://repo.uum.edu.my/9499/1/063.pdf http://repo.uum.edu.my/9499/ http://ieeexplore.ieee.org.eserv.uum.edu.my/xpl/articleDetails.jsp?tp=&arnumber=6316622&queryText%3Dfaudziah+ahmad |
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Summary: | Face recognition is one of the most interesting applications in the image processing field.To build a model to recognize the face of different people, we need to do several processes on the image to obtain the most efficient features.In this research a face recognition model is developed.The dataset used is of different face images. Neural Networks technique, specifically Multilayer Perceptron (MLP) model with Back-Propagation learning algorithm and Template Matching approach are implemented in model developed.The face recognition model developed is then applied on a remote database backup system.Template matching approach is found to give a higher percentage of matching accuracy and a faster result can be obtained compared to MLP as no learning process is required |
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