Automatic power line extraction algorithm in complex scene

doi:10.13474/j.cnki.11-2246.2021.0231

Abstract

Abstract: End-to-end power line extraction from aerial images in complex scenes is the key to power line detection by UAVs. In this paper, an automatic power line extraction algorithm based on improved Mask R-CNN is proposed by analyzing the problems existing in the realization of power line instance segmentation based on deep learning. First of all, according to the linear characteristic of power line, this paper puts forward a kind of improved Mask R linear IoU calculation method, a CNN original IoU calculation, improve the performance of power line extraction. Then the improved network on the power line data set for training, power line crude extraction results. Finally through a line marshalling fitting method, the result of the crude extract clustering fitting, to solve the problem of power line breakage and misdetection. Experimental results show that the proposed method can accurately extract the complete power lines from UAV aerial images with complex environment.

Key words: power line extraction, UAV, Mask R-CNN, linear IoU, line segment group fitting

CLC Number:

ZHAO Yanfeng, HU Yaogai, WANG Xianpei, ZHAO Le. Automatic power line extraction algorithm in complex scene[J]. Bulletin of Surveying and Mapping, 2021, 0(8): 1-6.

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