An automatic ellipse and line targets detection method from synthetic aperture sonar images

Wei Liu; Bao-Li Li; Ji-Yuan Liu; Chun-Hua Zhang

doi:10.1117/12.832935

30 October 2009 An automatic ellipse and line targets detection method from synthetic aperture sonar images

Wei Liu, Bao-Li Li, Ji-Yuan Liu, Chun-Hua Zhang

Proceedings Volume 7495, MIPPR 2009: Automatic Target Recognition and Image Analysis; 74953B (2009) https://doi.org/10.1117/12.832935
Event: Sixth International Symposium on Multispectral Image Processing and Pattern Recognition, 2009, Yichang, China

Abstract

Detection of ellipse and line targets is important for the analysis of Synthetic Aperture Sonar (SAS) images. An automatic ellipse and line targets detection method from synthetic aperture sonar images is presented. The method mainly has three procedures: preprocessing of SAS images, Zernike Orthogonal Moment Edge Detection Algorithm (ZOMEDA), line and ellipse detection. The guidance is presented firstly on how to perform the preprocessing of SAS images. Then, ZOMEDA is utilized to produce edge points with both the direction and position information. Principles of ZOMEDA with the 7x7 template are analyzed and the coefficients to carry out the ZOMEDA are calculated and listed. The idea of Random Sample Consensus (RANSAC) is applied to the Line and ellipse detection procedure to improve the robustness and the computing efficiency. Detail procedures of RANSAC are analyzed in the article. Calculating of line and ellipse parameters is pivotal to carry out the idea of RANSAC. Principles are analyzed on how to calculate the parameters of the line and ellipse based on the direction and position information. Another important procedure, parameters refinement, is also discussed. At last, the line and ellipse detection method is applied to simulated datasets and lake-trial datasets for validation.

Citation Download Citation

Wei Liu, Bao-Li Li, Ji-Yuan Liu, and Chun-Hua Zhang "An automatic ellipse and line targets detection method from synthetic aperture sonar images", Proc. SPIE 7495, MIPPR 2009: Automatic Target Recognition and Image Analysis, 74953B (30 October 2009); https://doi.org/10.1117/12.832935

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