AN AFFINE INVARIANT EULIDEAN DISTANCE BETWEEN IMAGES
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.
Annulus Eulidean distance Eulidean distance (ED) optical character recognition texture retrieval image metric
MELODY Z.W.LIAO JUN-YAN WANG WU-FAN CHEN YUAN Y.TANG
School of Applied Math, University of Electronic Science and Technology of China;Key Lab of Medical School of Communication & Information Engineering, University of Electronic Science and Technology o Key Lab of Medical Imaging, School of Biomedical Engineering, Southern Medical University, Guangzhou School of Computer Science, Chongqing University;Department of Computer Science, Hong Kong Baptist U
国际会议
2006 International Conference on Machine Learning and Cybernetics(IEEE第五届机器学习与控制论坛)
大连
英文
4133-4137
2006-08-13（万方平台首次上网日期，不代表论文的发表时间）