文献类型：期刊文献

英文题名：Nonlinear circumference-based robust ellipse detection in low-SNR images

作者：Wang, Zhuoran[1];Yi, Jianjun[1];Ding, Hongkai[1];Zeng, Fei[1];Mu, Jinzhen[2,3];Wu, Bin[4]

机构：[1]East China Univ Sci & Technol, Dept Mech Engn, Shanghai 200237, Peoples R China;[2]Shanghai Aerosp Control Technol Inst, Shanghai 201109, Peoples R China;[3]Shanghai Key Lab Aerosp Intelligent Control Techno, Shanghai 201109, Peoples R China;[4]Aerosp Syst Engn Shanghai, 3888 Yuanjiang Rd,Minhang Dist, Shanghai 201109, Peoples R China

年份：2024

卷号：144

外文期刊名：IMAGE AND VISION COMPUTING

收录：;EI(收录号：20241215774438);WOS:【SCI-EXPANDED(收录号:WOS:001220705600001)】；

语种：英文

外文关键词：Ellipse detection; Nonlinear circumference; Hough transform; Low-SNR images

摘要：This study aims to present an effective method to detect ellipses on images with low signal-to-noise ratios (SNR). Firstly, we analyze four major interferences caused by low SNR images. A nonlinear circumference-based ellipse detection method is proposed, which uses a nonlinear circumference to vote on the parameter space constructed from input images and a spatial hierarchical search strategy to find the optimum ellipse parameters. The nonlinear circumference is designed to describe the possibility that selected edge points will generate a given ellipse. Experiments on six low SNR datasets show that our method outperforms five existing methods in terms of recall, precision and F-measure. Furthermore, a definition based on the nonlinear circumference is proposed to quantify SNR of synthetic images with ellipses. Experimental results demonstrate that our method can detect ellipses on images close to 0.2 dB while state-of-the-art methods can almost only reach 1.2 dB.