Share Email Print
cover

Proceedings Paper

A new robust gradient-based method for detection of symmetry axis
Author(s): Jing Hu; Qinqi Wan; Yongli Hu
Format Member Price Non-Member Price
PDF $14.40 $18.00
cover GOOD NEWS! Your organization subscribes to the SPIE Digital Library. You may be able to download this paper for free. Check Access

Paper 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.

Paper Details

Date Published: 14 December 2015
PDF: 7 pages
Proc. SPIE 9812, MIPPR 2015: Automatic Target Recognition and Navigation, 98120Y (14 December 2015); doi: 10.1117/12.2209235
Show Author Affiliations
Jing Hu, Huazhong Univ. of Science and Technology (China)
Qinqi Wan, Huazhong Univ. of Science and Technology (China)
Yongli Hu, Huazhong Univ. of Science and Technology (China)


Published in SPIE Proceedings Vol. 9812:
MIPPR 2015: Automatic Target Recognition and Navigation
Nong Sang; Xinjian Chen, Editor(s)

© SPIE. Terms of Use
Back to Top