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Link to original content: https://doi.org/10.1587/elex.6.1112
2009 Volume 6 Issue 15 Pages 1112-1117
This paper proposes an improvement to the Eigenphases method, in which the image is normalized to reduce the illumination and facial expression effects and the Principal Components Analysis (PCA) is used for feature extraction, while the Gaussian Mixture Model (GMM)is used to improve the performance of classification stage. An important advantage of GMM is that this system is trained without supervisor and constructs an independent model for each user. The proposed method is evaluated using the ”AR Face Database”, which includes the face images of 120 subjects (65 males and 55 females). Evaluation results show that the proposed method provides better performance than the original eigenphases method.
