An effective color space for face recognition

Abstract

The three color components specifying a color can be defined in various ways leading to significantly different classification abilities. Several effective color spaces including RQCr, DCS and ZRG have been proposed to achieve better face recognition performance. However, their performance is not consistent on different databases. What's more, the framework of effective color spaces has not been thoroughly studied yet. In this paper, we propose an effective color space LC\C2 based on a framework of effective color spaces. LC\C2 consists of one discriminant luminance component L and two discriminant chrominance components C\C2. To find the discriminant luminance component, 4 luminance components from existing effective color models are compared. After that, the weighted color space normalization technique (WCSN) is applied on the DCS color space to generate two complementary and discriminative chrominance components. Experiments conducted on three databases (FRGC, AR and CMU Multi-PIE) show that the proposed color space LC\C2 achieves the best face recognition performance consistently.