Abstract
Current methods for insulator extraction are mostly used for aerial imagery. There are few insulator extraction methods suitable for live working robots on mobile platforms. This paper proposes an insulator segmentation method based on depth image and color image (ISBDC). Firstly, ISBDC divides the image according to the depth information acquired by the depth camera, and removes the background image with a long distance to obtain the approximate position of the insulator in the image. Then, using OSTU to extract contours of the insulator. Finally, according to the distribution of the pixels, the background noise is further removed and the small connected region is deleted to get the final result. Compared with other algorithms, ISBDC can suppress more background noise (especially when there are multiple interference insulators in the image) and obtain enough insulator details while ensuring simple structure and not requiring much data to train.
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Acknowledgments
This work is supported by the National Natural Science Foundation of China under Grants 61873248, the Hubei Provincial Natural Science Foundation of China under Grant 2017CFA030 and Grant 2015CFA010, and the 111 project under Grant B17040, the Science and Technology Project of State Grid Corporation of China under Grant 52153216000R.
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He, W., Chen, X., Jian, X. (2019). An Insulator Image Segmentation Method for Live Working Robot Platform. In: Yu, H., Liu, J., Liu, L., Ju, Z., Liu, Y., Zhou, D. (eds) Intelligent Robotics and Applications. ICIRA 2019. Lecture Notes in Computer Science(), vol 11742. Springer, Cham. https://doi.org/10.1007/978-3-030-27535-8_46
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DOI: https://doi.org/10.1007/978-3-030-27535-8_46
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