A new method for power line detection based on computer graphics algorithms is presented. The algorithm uses geometric relationships that are inherent to the circle symmetry. The method detects line segments that are linked in a posterior stage. For the detection, we use Canny and Steerable Filters. We developed two tests for validating the proposed approach. The first one uses synthetic images and the second one real power line images taken from UAVs. The results show that this method is not only efficient for line detection, but it also takes compared with state of the art algorithms a short computing time without the use of a GPU approach.

In this study, the authors propose a new method for transmission tower detection that involves the use of visual features and the linear content of the scene. For this process, they developed a descriptor based on a grid of two‐dimensional feature descriptors that is useful not only for object detection, but also for tracking the area of interest. For the detection and classification, they used a support vector machine. The experiments were conducted with a dataset of real world images from transmission tower videos that were used to validate the strategy by comparing it with the ground truth. The results showed that the obtained method is fast and appropriate for tower detection in video sequences of environments that include rural and urban areas. The detection took less than 50 ms and was faster than other methods.

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