An Efficient Wavelet Based Feature Extraction Method for Face Recognition
ISNN 2009 Proceedings of the 6th International Symposium on Neural Networks: Advances in Neural Networks - Part III
Face recognition using Zernike and complex Zernike moment features
Pattern Recognition and Image Analysis
2.5D face recognition using Patch Geodesic Moments
Pattern Recognition
Discriminative Zernike and Pseudo Zernike Moments for Face Recognition
International Journal of Computer Vision and Image Processing
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Human face recognition has recently become one of the hottest topics in the area of pattern recognition due to its applications in identity validation and recognition. Moment Invariants are pattern sensitive features and are used in pattern recognition applications. In this paper different moment invariants have been used to extract features from human face images for recognition application. Moment invariants of Hu (HMI), Bamieh (BMI), Zernike (ZMI), Pseudo Zernike (PZMI), Teague-Zernike (TZMI), Normalized Zernike (NZMI) ,Normalized Pseudo Zernike (NPZMI) and also regular Moment Invariant (RMI) have been applied to the AT&T face database and the results have been compared. Our results show that pseudo Zernike moments yields the best recognition accuracy of 95%.