Abstract
The region proposal algorithm for line insulators is a critical step in line insulator detection. The selective search algorithm provides a rich candidate area for line insulators. However, the selective search algorithm uses SIFT descriptor to extract texture features. It causes a large time overhead. In response to this problem, this paper proposes an improved algorithm. The algorithm use the Harr-Like algorithm to form a feature value map. Then, the formed feature value map is mapped to a fixed-size texture vector HBSN (Harr-Like Based on SPP-Net) by using Spatial Pyramid Pooling Network. In the process of the formation of feature maps and the construction of feature vectors, the integral image is used for acceleration. The integral image can only traverses the pixels in the original image once, forming an integral image of the feature values corresponding to the original image. When calculating the texture vector of different regions in the original image, it only needs to index the corresponding position of the eigenvalue integral image, which overcomes the problem of repeated calculation of texture features in the overlapping region by selective search and achieves fast calculation of texture similarity in different regions.
Experiments show that the improved selective search algorithm for line insulator has a calculation speed increase of 8.21% compared with the selective search.
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Acknowledgement
This research is partially supported by:
1. Research Foundation of Education Bureau of Jilin Province (JJKN20190710KJ).
2. Science and Technology Innovation Development Plan Project of Jilin city (20190302202).
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Guo, S., Yue, B., Bai, Q., Lin, H., Zhou, X. (2020). Region Proposal for Line Insulator Based on the Improved Selective Search Algorithm. In: Sun, X., Wang, J., Bertino, E. (eds) Artificial Intelligence and Security. ICAIS 2020. Lecture Notes in Computer Science(), vol 12240. Springer, Cham. https://doi.org/10.1007/978-3-030-57881-7_60
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