Automatic Detection Method of Target Axis and Mark Ring Based on Edge Optimization and Line Screening
Aiming at the problem that traditional target contour and central axis detection algorithms are easily affected by factors such as non-uniform backgrounds, incomplete target imaging, and tail flame interference, which can lead to deviations in the central axis and mass center, an automatic detection method for the object central axis and mark rings based on edge optimization and line screening is proposed. Firstly, the frame difference algorithm is combined with canny algorithm to initially locate the ROI region of the moving target. Then, an improved edge detection algorithm based on the OTSU method is used to automatically extract the effective edges. Firstly, the frame difference algorithm is combined with the canny algorithm to initially locate the ROI region of the moving target. Then, an improved edge detection algorithm based on the OTSU algorithm is used to automatically extract the effective edges. After that, the target attitude interval and length threshold are calculated using EDLines algorithm, and the central axis is selected based on hough transform and line screening criteria. Finally, the mark rings are detected through RGB image segmentation and morphological operations, and their intersections with the central axis are used as the feature points. The experimental results show that the proposed method has obvious advantages over the traditional algorithms in engineering application, detection efficiency and accuracy.
Authors
- Mingwei Gao (ORCID: https://orcid.org/0000-0002-5612-4251)
- Jing Cao (ORCID: https://orcid.org/0000-0002-9485-4204)
- Kai Wang (ORCID: https://orcid.org/0000-0001-8923-1232)
- Junbiao Chen
- Xinrui Yang (ORCID: https://orcid.org/0009-0008-8917-9831)
Institutions
- Beijing Institute of Technology (CN)
- China North Industries Group Corporation (China) (CN)
Publication Details
- Published
- 2024-11-22
- DOI
- https://doi.org/10.1109/icicml63543.2024.10958023
- Primary Topic
- Image and Object Detection Techniques
- Type
- article
- Field-Weighted Citation Impact
- 0.00