Illumination normalization for face recognition using the census transform

Abstract

A problem with face recognition is that lighting conditions can affect performance since facial features are easily distorted by varying illumination conditions. To address this problem, we present a new preprocessing method using the census transform. In the proposed method, we generate a number of binary values from the current pixel by comparing it with the neighbor pixels, and encode the binary values into a single gray scale image. Finally, we apply the principal component analysis (PCA) to the gray scale images. Experiments show that the proposed method provides promising results.