Abstract:
In this paper, an adaptive technique using Firefly
Algorithm for feature selection in face recognition is proposed.
The artificial fireflies are designed to represent the feature subset
and they move in a hyper dimensional space to obtain the best
features. The features are extracted using Discrete Cosine
Transform (DCT) and Haar wavelets based Discrete Wavelet
Transform (DWT). The algorithm is validated using benchmark
face databases namely ORL and Yale. The proposed algorithm
outperforms various existing techniques. The average recognition
accuracy using five randomly selected training samples over four
independent runs for the ORL is 94.375%. The accuracy using
six training images for Yale face database is 99.16%. The effect
of parameter 'gamma', specific to Firefly Algorithm on
recognition accuracy is also investigated.