In this paper, a system is proposed for extracting insulators on power transmission lines from photographs captured by an unmanned aerial vehicle. The approximate regions of the insulators are first determined by a support vector machine with the histogram of oriented gradients as the feature descriptor. Then, the specific regions of insulators are detected and extracted by the GrabCut algorithm. In advance, some constraint conditions, such as the value ranges of color component values as well as the relationships between the component values in three color models, need to be specified. In our system, an interactive interface is developed to help determine these conditions. According to the experimental results, our system is capable of removing most of the backgrounds and extracting the insulators from photographs.
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The author (Chi Zhang) appreciates the financial support of China Scholarship Council during his study at Kyoto University.
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Zhang, C., Gong, Q., Wang, T. et al. Visual extraction system for insulators on power transmission lines from UAV photographs using support vector machine and color models. J Vis (2020). https://doi.org/10.1007/s12650-020-00672-9
- Insulator extraction
- Support vector machine
- Color model
- Image processing
- Pattern recognition