This paper proposes a novel concept of Local AutoCorrelation (LAC), which is converted to LAC images for robust face detection under varying illumination conditions. We have applied LAC images to face detection based on AdaBoost algorithm. MIT CBCL images are used for training, while CMU PIE face database including a variety of illumination directions is used for detection. As a result, the LAC is found to be so effective that face detection rate is improved by up to 4.7%.