Embedded face recognition based on fast genetic algorithm for intelligent digital photography

In this paper, we propose embedded face recognition (FR) to use in intelligent image system. For efficient FR VLSI design, we use a feature selection and feature extraction method based on Gabor wavelets using a fast genetic algorithm (FGA). Many FR systems are based on Gabor wavelet due to its desirable characteristics of spatial locality and orientation selectivity. However, the process of searching for features with Gabor wavelet is computationally expensive and has an unusual sensibility for variations such as illumination. To overcome these problems and use in real-time applications, we optimize Gabor wavelet's parameters of translation, orientations and scales, which make it approximates a local image contour region by the use of hardware oriented FGA. From experimental results, we certify that our method shows recognition rate of over 97.27 % for FERET dataset, which exceeds the performance of the other popular methods