Texture-Based Eyebrow Recognition

Abstract

Recent studies show that eyebrows can be used as a biometric or soft biometric for recognition. In some scenarios such as partially occluded or covered faces, they can be used for recognition. In this paper, we study eyebrow recognition using texture-based features. We apply features which have not been used before for eyebrow recognition such as 3-patch local binary pattern and WLD (Weber local descriptor) features. Also, we use more conventional features such as uniform LBP (Local binary pattern) and HOG (Histograms of oriented gradients). Methods are tested on both small- and large-sized datasets of images taken from FRGC database. Our experiments show that using some of these texture-based features together increases the performance significantly. We achieved more than 95% recognition accuracy for left and right eyebrows.