Algorithm of face recognition by principal component analysis
A face recognition algorithm based on Principal Component Analysis (PCA) has been developed and tested for computer vision applications. A database of about 400 facial images was used to test the algorithm. Each image is represented by a matrix (112x 92). The database is divided into subsets, where...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
IIUM Press
2002
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| Subjects: | |
| Online Access: | http://irep.iium.edu.my/5779/ http://irep.iium.edu.my/5779/1/ALGORITHM_OF_FACE_RECOGNITION_BY_PRINCIPAL_COMPONENT_ANALYSIS.pdf |
| Summary: | A face recognition algorithm based on Principal Component Analysis (PCA) has been developed and tested for computer vision applications. A database of about 400 facial images was used to test the algorithm. Each image is represented by a matrix (112x 92). The database is divided into subsets, where each subset represents one of 10 different individuals. A 96% rate of successful detection and a 90% rate of successful recognition were obtained. Several factors had to be standardized to provide a constrained environment in order to reduce error. The analysis is based on a set of eigenvectors that defines an Eigen Face (EF). The method proved to be simple and effective. The simplified algorithm and techniques expected the process without seriously compromising the accuracy. |
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