Low-cost multi-spectral face imaging for robust face recognition

Abstract

Multi-spectral face recognition has acquired significant attention over a last few decades due to its potential of capturing spatial and spectral information across the electromagnetic spectrum. In this paper, we present a new imaging scheme that can obtain the multi-spectral face image at nine different spectra covering 530nm–1000nm. We prepared a new database comprising of 230 subjects using our new low-cost multi-spectral face imaging device. Extensive experiments are presented for evaluating the performance of the four different state-of-the-art face recognition algorithms on both individual bands and the fused spectral face image. Obtained results show the improved face recognition performance of Log-Gabor features with Collaborative Representation (CRC) as the classifier.