文献类型：期刊文献

英文题名：Orthogonal moments based on exponent functions: Exponent-Fourier moments

作者：Hu, Hai-tao[1];Zhang, Ya-dong[1];Shao, Chao[1];Ju, Quan[1]

第一作者：Hu, Hai-tao

通讯作者：Hu, HT[1]

机构：[1]Henan Univ Econ & Law, Coll Comp & Informat & Engn, Zhengzhou 450002, Peoples R China

第一机构：河南财经政法大学计算机与信息工程学院

通讯机构：[1]corresponding author), Henan Univ Econ & Law, Coll Comp & Informat & Engn, Zhengzhou 450002, Peoples R China.|[1048412]河南财经政法大学计算机与信息工程学院;[10484]河南财经政法大学;

年份：2014

卷号：47

期号：8

起止页码：2596-2606

外文期刊名：PATTERN RECOGNITION

收录：;EI(收录号：20141817669735);Scopus(收录号：2-s2.0-84899471277);WOS:【SCI-EXPANDED(收录号:WOS:000336341200003)】；

基金：This work was supported by the National Natural Foundation of China (Grant nos. 61065004 and 61202285), the Key Science&Technology Research Fund of Henan Provincial Educational Department (Nos. 148520020 and 13A520033).

语种：英文

外文关键词：Exponent-Fourier moments; Zernike moments; Image analysis; Bessel-Fourier moments; Radial harmonic Fourier moments; Polar Harmonic Transforms

摘要：In this paper, we propose a new set of orthogonal moments based on Exponent functions, named Exponent-Fourier moments (EFMs), which are suitable for image analysis and rotation invariant pattern recognition. Compared with Zernike polynomials of the same degree, the new radial functions have more zeros, and these zeros are evenly distributed, this property make EFMs have strong ability in describing image. Unlike Zernike moments, the kernel of computation of EFMs is extremely simple. Theoretical and experimental results show that Exponent-Fourier moments perform very well in terms of image reconstruction capability and invariant recognition accuracy in noise-free, noisy and smooth distortion conditions. The Exponent-Fourier moments can be thought of as generalized orthogonal complex moments. (C) 2014 Published by Elsevier Ltd.