In this paper, we propose a novel affine invariant Eulidean Distance of images, named annulus Eulidean Distance (AED). Unlike the traditional Eulidean distance, the AED takes into account the spatial correlation between images. Therefore, it is invariant to the scale, rotation and shift transformation for images. The method is motivated that the annulus is intuitively rotation invariant, then combined with the centralization and normalization of the images, the AED is variant to affine transformation (AT). The key advantage of this distance is that it is a simple and tractable way to measure the difference between images with some deformations. Some examples in Optical Character Recognition (OCR) and Texture Retrieval are presented to show the power of the AED. Experimental results demonstrate that the AED is a simple, efficient and powerful way to measure the difference between images.