Powerline detection for aircraft flight safety using image processing

In this thesis, several active methods have been proposed for the safety of air vehicles, which prevent air vehicles from colliding with electrical wires. In this context, Discrete Cosine Transform, Linear Binary Pattern, Histogram of Gradient and Convolutional Neural Network methods were used. The methods were tested on image databases, which consist of real life aerial images that were captured and curated by ourselves. The recognition performances of such scenes with these methods were compared. The effects of various pre-processing / pre-training on the classification and feature extraction steps were also examined.