Visible Light Face Images Research Articles

Illumination Uniformity Evaluation on Visible Light andNear-Infrared Face Images

In this paper, illumination uniformity on face images has been accessed. A database of 1056 visible light face images and 1056 near-infrared face images has been used in our assessment process. This database uses 22 volunteers, irrespective to race and gender. Each volunteer had to attend two photography sessions. Our investigation on intensity distributions, and intensity differences, supports the theory that near-infrared face images are more robust towards illumination variations.

Wavelet-based multispectral face recognition

This paper proposes a novel wavelet-based face recognition method using thermal infrared (IR) and visible-light face images. The method applies the combination of Gabor and the Fisherfaces method to the reconstructed IR and visible images derived from wavelet frequency subbands. Our objective is to search for the subbands that are insensitive to the variation in expression and in illumination. The classification performance is improved by combining the multispectal information coming from the subbands that attain individually low equal error rate. Experimental results on Notre Dame face database show that the proposed wavelet-based algorithm outperforms previous multispectral images fusion method as well as monospectral method.