文献类型：期刊文献

英文题名：A complete set of pseudo-Zernike moment invariants by image shape description

作者：Zheng, Lin[1]; Zhao, Sinan[2]; Liu, Qian[1]; Zhu, Hongqing[1]

机构：[1] Department of Electronics and Communications Engineering, East China University of Science and Technology, Shanghai 200237, China; [2] Department of Information and Control Engineering, Shanghai University of Electric Power, Shanghai 200090, China

年份：2012

卷号：7530 LNAI

起止页码：775

外文期刊名：Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

收录：EI(收录号：20124515642372)

语种：英文

外文关键词：Feature extraction - Computer vision

摘要：Orthogonal moments such as pseudo-Zernike moments have been successfully used in the field of image analysis. Conventionally, image function is mapped onto a set of orthogonal functions over the unit circle. If the origin of polar coordinate system is taken at the centroid, the rotation invariants will be easy to obtain. Based on pseudo-Zernike moments, this paper presents a new method to drive the complete rotation, scaling and translation (RST) invariants from the orthogonal projection transform (OPT). The efficiency and the robustness to different noises of the method for classification tasks are presented by comparing it with several existing methods. ? 2012 Springer-Verlag.