Conventional methods to detect changes between temporal images are subject to the effect of illumination variance and registration noise. The method proposed in this paper uses the edge structure information in image to detect changes. A new conception based on biological vision principle, named Edge Token, is introduced to describe the edge structure, which is extracted by using a set of Gabor functions on the intensity map of gradient image. Correlation is used to compare the similarity of two Edge Token vectors. In order to reduce the false alarm, a suppression factor is taken to reduce the effect of weak edges. According to the result of the correlation process, decision rule can be made to locate the outline of changed area. The Edge Token based change detection is robust to illumination variance and registration noise. Experiments on simulated data and remote sensing images are presented.