A new robust gradient-based method for detection of symmetry axis

Jing Hu; Qinqi Wan; Yongli Hu

doi:10.1117/12.2209235

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14 December 2015 A new robust gradient-based method for detection of symmetry axis

Jing Hu, Qinqi Wan, Yongli Hu

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Proceedings Volume 9812, MIPPR 2015: Automatic Target Recognition and Navigation; 98120Y (2015) https://doi.org/10.1117/12.2209235
Event: Ninth International Symposium on Multispectral Image Processing and Pattern Recognition (MIPPR2015), 2015, Enshi, China

Abstract

Symmetry axis extraction is an important part of the image feature detection. So far, various classical symmetry axes extraction algorithms have been proposed, such as the minimum-inertia-axis-based method, the SIFT-based method. If the input image is blurry, or it’s difficult to extract feature points or corner points from input images, however, the above algorithms are difficult to obtain satisfied results. This paper presents a gradient-based method that can robustly extract symmetry axis from visual pattern. The key points of our methods are gradient calculation, symmetric weight calculation, and Hough Transform. Our method was evaluated on several datasets, including both blurred and smooth-edged cases. Experimental results demonstrated that our method achieves a more robust performance than previous methods.

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Jing Hu, Qinqi Wan, and Yongli Hu "A new robust gradient-based method for detection of symmetry axis", Proc. SPIE 9812, MIPPR 2015: Automatic Target Recognition and Navigation, 98120Y (14 December 2015); https://doi.org/10.1117/12.2209235

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