Transmission Line Detection Based on Improved Hough Transform
This work addresses transmission line detection for UAV-based monitoring, presenting an incremental improvement over existing Hough transform techniques.
The paper tackled the problem of low accuracy and high false positives in detecting transmission lines from UAV images by introducing an enhanced stochastic Hough transform method, resulting in improved detection accuracy and faster processing compared to conventional methods.
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.