Using Quotient Image and Linear Subspace for Face Recognition under Arbitrary Illumination Conditions

In this paper, we theoretically analyze the limitation of the Quotient Image (QI) method proposed by Shashua and present a new way to compute the quotient image. Based on the observation that nine basis point light sources can represent almost arbitrary lighting conditions for face recognition application, we use the corresponding nine basis images which are all real images to span the image space. And similar to the QI, our method can not only get an illumination invariant image but also synthesize a new image under arbitrary illumination conditions. We provide an experimental result to show the effectiveness of our algorithm as well.