Author(s)

Behzad Bozorgtabar, Gholam Ali Rezai Rad

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Increasing demand for a fast and reliable face recognition technology has obliged researchers to try and examine different pattern recognition schemes. But until now, Genetic Programming (GP), acclaimed pattern recognition, data mining and relation discovery methodology, has been neglected in face recognition literature. This paper tries to apply GP to face recognition. First Principal Component Analysis (PCA) is used to extract features, and then GP is used to classify image groups. To further improve the results, a leveraging method is also utilized. It is shown that although GP might not be efficient in its isolated form, a leveraged GP can offer results comparable to other Face recognition solutions.

Face Recognition, Principal Component Analysis, Genetic Programming, Leveraging Algorithm

B. Bozorgtabar and G. Rad, "A Genetic Programming-PCA Hybrid Face Recognition Algorithm," Journal of Signal and Information Processing, Vol. 2 No. 3, 2011, pp. 170-174. doi: 10.4236/jsip.2011.23022.