Comparison of Face Recognition Techniques
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چکیده
In [2] feature graphs based on a wavelet transform, principle component analysis (PCA), and linear discriminant analysis (LDA) are compared. They reported 88%, 85% and 56% accuracy for PCA, LDA, and Gabor Wavelets respectively with a database containing 20 and individuals varying in gender, age, pose, and race. For each individual five images were used for testing, while one images was employed as the learning sample. Efficiency of face recognition tested on positive and negative samples was reported best for PCA followed by LDA. Gabor wavelets performed worst.
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