This paper proposes a detection method of artificial obstacles from a single image. The proposed method first detects local lines as candidates based on the duality of gradient orientation and then globally determines whether they are artificial obstacles by using fractal dimension and the perimeter of the region. The proposed method has two distinct advantages: (1) the accurate detection of artificial obstacles in the form of not only straight lines but also curved lines, and (2) the fast detection of obstacles by using hysteresis thresholding at the global detection phase. Results with real images are presented to illustrate the superior performance of the proposed method.
