Transmission Line Detection Based on Improved Hough Transform
Wei Song Pei Li Man Wang
To address the challenges of low detection accuracy and high false positive
rates of transmission lines in UAV (Unmanned Aerial Vehicle) images, we explore
the linear features and spatial distribution. We introduce an enhanced
stochastic Hough transform technique tailored for detecting transmission lines
in complex backgrounds. By employing the Hessian matrix for initial
preprocessing of transmission lines, and utilizing boundary search and pixel
row segmentation, our approach distinguishes transmission line areas from the
background. We significantly reduce both false positives and missed detections,
thereby improving the accuracy of transmission line identification. Experiments
demonstrate that our method not only processes images more rapidly, but also
yields superior detection results compared to conventional and random Hough
transform methods.