Abstract
Aiming at the problem of inaccurate edge detection caused by reflection on workpiece metal surface, a method of eliminating metal reflection area in image was proposed to deal with the reflection area. Then the image is optimized by particle swarm optimization adaptive edge detection to improve the speed and accuracy of edge detection results.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Tang, Z.: Defect detection of sheet metal parts based on machine vision, no. (09), pp. 1–6. Hunan University (2021)
Forbus, K.: Light source effects. Technical report. AI Memo AIM-422, Massachusetts Institute of Technology (1977)
Brelstaff, G., Blake, A.: Detecting specular reflections using Lambertian constraints. In: Proceedings of the 2nd International Conference on Computer Vision, pp. 297–302 (1988)
Gershon, R., Jepson, A.D., Tsotsos, J.K.: The use of color in highlight identification. In: Proceedings of the 10th International Joint Conference on Artificial Intelligence, vol. 2, pp. 752–754 (1987)
Klinker, G., Shafer, S., Kanade, T.: Using a color reflection model to separate highlights from object color. In: Proceedings of the 1st International Conference on Computer Vision, pp. 145–150 (1987)
Arnold, M., Ghosh, A., Ameling, S., Lacey, G.: Automatic segmentation and inpainting of specular highlights for endoscopic imaging. EURASIP J. Image Video Process. 2010, 2–3 (2010)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2024 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
About this paper
Cite this paper
Wang, Y., Wang, C. (2024). Review of Edge Detection Methods for Reflective Metal Surfaces of Workpieces. In: Wang, Y., Yu, T., Wang, K. (eds) Advanced Manufacturing and Automation XIII. IWAMA 2023. Lecture Notes in Electrical Engineering, vol 1154. Springer, Singapore. https://doi.org/10.1007/978-981-97-0665-5_10
Download citation
DOI: https://doi.org/10.1007/978-981-97-0665-5_10
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-97-0664-8
Online ISBN: 978-981-97-0665-5
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)