Auto-Identification of Symmetrical Contours on ICT Image in Reverse Engineering

Article Preview

Abstract:

Through considering the symmetry constraint characteristics in mechanical product contours, an auto-identification method of two-dimensional symmetrical contour based on feature matching is presented in this paper. Firstly, the feature points are extracted based on contour cloud point data partition and by using offset method, the different distribution rules of axis-symmetrical and rotation-symmetrical images for judging the type of symmetry was studied. The feature description parameters of symmetrical contour were calculated by adopting rotational inertia method and periodic method, which is regarded as the parameters for solving overall constraint optimization of the contour. Examples show that the proposed method can effectively identify the symmetrical contours and their types, and accurately extract the symmetrical constraint features.

You might also be interested in these eBooks

Info:

Periodical:

Pages:

1341-1346

Citation:

Online since:

September 2013

Export:

Price:

Permissions CCC:

Permissions PLS:

Сopyright:

© 2013 Trans Tech Publications Ltd. All Rights Reserved

Share:

Citation:

[1] SUN Jie, ZHAI Hongchen, TANG Yiliang, et al. Positioning and extraction of feature area for symmetry object in target recognition[J]. Journal of Optoelectronics. laser, 2001( 6): 623-626.

Google Scholar

[2] ZHANG Xu, ZHU Weidong, KE Yinglin. Constraint reconstruction theory of 2D symmetry geometry model its application in reverse engineering[J]. Chinese Journal of Mechanical Engineering, 2007(4): 77-82.

DOI: 10.3901/jme.2007.04.077

Google Scholar

[3] WU Dingxue, GONG Junbin, XU Hongbo, et al. New algorithm of image rotation matching based on feature points[J]. Computer Science, 2009(12): 248-250, 262.

Google Scholar

[4] YU Guangbin, LI Zongmin, LIU Yujie, et al. Recognition of 2D axis symmetry shapes based on moment invariants[J]. Computer Engineering and Applications, 2006(29): 38-40, 54.

Google Scholar

[5] Nahum Kiryati, Yossi Gofman. Detecting symmetry in grey level images: the global optimization approach[J]. International Journal of Computer Vision, 1998, 29(1): 29-45.

DOI: 10.1109/icpr.1996.546152

Google Scholar

[6] Guo Shuxiang, Qiu Chenguang, Ye Xiufen. A kind of global motion estimation algorithm based on feature matching[J]. Proceedings of the 2009 IEEE International Conference on Mechatronics and Automation, 2009: 107-111.

DOI: 10.1109/icma.2009.5246379

Google Scholar

[7] ZHANG Wenjing, XU Xiaoming, SU Jianfeng.  An improved algorithm for 2D shape matching based on Hausdorff distance[J]. Journal of Image and Graphics, 2000(2): 106-109.

Google Scholar