基于视觉显著性的输电线路杆塔鸟窝检测

BIRD'S NEST DETECTION OF TRANSMISSION LINES TOWER BASED ON VISUAL SALIENCY

  • 摘要: 鸟类在输电线路杆塔上筑巢会对电网的稳定运行造成极大的威胁。针对无人机航拍图像中鸟窝检测问题,提出一种基于视觉显著性的输电线路杆塔鸟窝检测算法,该算法通过灰度值分析定位出线路杆塔所在的区域并将其作为感兴趣区域,提取图像的三种显著性特征,并采用条件随机场模型进行特征融合得到显著图;根据鸟窝的形状特征制定约束条件,排除电力线和云层等伪目标的干扰,得到鸟窝检测结果。实验结果表明,所提出的方法能够准确地检测出输电线路杆塔上的鸟窝。

     

    Abstract: Bird nesting on the transmission line towers will bring a great threat to the stable operation of power grids. Aimed at the problem of bird's nest detection in aerial images taken by UAV, a detection method for bird's nest on the transmission line towers based on visual saliency is proposed. The area of transmission tower was located by gray value analysis and is regarded as the region of interest. Three salient features were extracted from the region of interest in the image, and the conditional random field model was adopted to fuse these three salient features to obtain the saliency map. The constraint set by the shape of bird's nest was used to eliminate pseudo-targets such as power lines and clouds. Experimental results show that the proposed algorithm can effectively detect the bird's nest on the transmission line tower.

     

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