Human face recognition using random forest based fusion of a trous wavelet transform coefficients from thermal and visible images
Abstract This paper presents a new image fusion algorithm based on the visible and thermal IR face images, which exploits the advantages of both kinds of images. The proposed fusion algorithm utilizes the translation invariant a trous wavelet transform and random forest (RF) classifier to decide the contribution of the visible and thermal IR face images in the formation of fused images. The Universal Image Quality Index is used to evaluate the quality of fused images and results are quite satisfactory. The fused face images are recognized by RF classifiers. The recognition performances of the proposed fusion scheme are 99.07% and 100% for UGC JU and IRIS benchmark face databases respectively, which is better than those if only visible or thermal IR faces are used.