Paper
24 October 2017 A robust recognition and accurate locating method for circular coded diagonal target
Yunna Bao, Yang Shang, Xiaoliang Sun, Jiexin Zhou
Author Affiliations +
Proceedings Volume 10458, AOPC 2017: 3D Measurement Technology for Intelligent Manufacturing; 104580Q (2017) https://doi.org/10.1117/12.2283523
Event: Applied Optics and Photonics China (AOPC2017), 2017, Beijing, China
Abstract
As a category of special control points which can be automatically identified, artificial coded targets have been widely developed in the field of computer vision, photogrammetry, augmented reality, etc. In this paper, a new circular coded target designed by RockeTech technology Corp. Ltd is analyzed and studied, which is called circular coded diagonal target (CCDT). A novel detection and recognition method with good robustness is proposed in the paper, and implemented on Visual Studio. In this algorithm, firstly, the ellipse features of the center circle are used for rough positioning. Then, according to the characteristics of the center diagonal target, a circular frequency filter is designed to choose the correct center circle and eliminates non-target noise. The precise positioning of the coded target is done by the correlation coefficient fitting extreme value method. Finally, the coded target recognition is achieved by decoding the binary sequence in the outer ring of the extracted target. To test the proposed algorithm, this paper has carried out simulation experiments and real experiments. The results show that the CCDT recognition and accurate locating method proposed in this paper can robustly recognize and accurately locate the targets in complex and noisy background.
© (2017) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Yunna Bao, Yang Shang, Xiaoliang Sun, and Jiexin Zhou "A robust recognition and accurate locating method for circular coded diagonal target", Proc. SPIE 10458, AOPC 2017: 3D Measurement Technology for Intelligent Manufacturing, 104580Q (24 October 2017); https://doi.org/10.1117/12.2283523
Lens.org Logo
CITATIONS
Cited by 2 scholarly publications.
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Target recognition

Back to Top