Abstract
Recently, the helicopter patrol is the main way in power system line patrol with the advantages of high efficiency and low cost. The aerial images are characterized by large in number, complex background, et cetera. It is necessary to segment insulator object from aerial images for better insulators’ fault diagnosis. The traditional single segmentation method causes user’s fatigue and results in bad segmentation quality. This paper proposes a cosegmentation method of aerial insulator images which utilizes the relationship between images that can improve the segmentation quality and reduce user’s workload. According to the thermodynamic anisotropic diffusion theory and the constructed graph network, we extract the corresponding largest relevant region by temperature maximization among the images as the common insulator objects. In order to achieve more accurate and fast segmentation, we remove the text, noises in aerial images and over-segment the preprocessed images into superpixels. Experiments show that the method can obtain good results which are instrumental to insulators’ fault diagnosis.
This work was supported by the National Natural Science Foundation of China under grant number 61401154.
This work was supported in part by the Fundamental Research Funds for the Central Universities under Grant No.2014ZD32.
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Qi, Y., Xu, L., Zhao, Z., Cai, Y. (2015). A Cosegmentation Method for Aerial Insulator Images. In: Tan, T., Ruan, Q., Wang, S., Ma, H., Di, K. (eds) Advances in Image and Graphics Technologies. IGTA 2015. Communications in Computer and Information Science, vol 525. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-47791-5_14
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DOI: https://doi.org/10.1007/978-3-662-47791-5_14
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