Symmetrical PCA in face recognition
نویسندگان
چکیده
Facial symmetry is obviously a useful natural characteristic of facial images, which will help develop face-oriented recognition technology and algorithms. This paper will apply it to face recognition after introducing mirror images. By combining PCA with the even-odd decomposition principle, a new algorithm called Symmetrical Principal Component Analysis is proposed, in which different energy ratios of even/odd symmetrical principal components and their different sensitivities to pattern variations are employed for feature selection. This algorithm has two outstanding advantages. Firstly, it effectively improves the stability of features and remarkably raises the recognition rate. Secondly, it greatly saves the computational and memory cost.
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