Fractal based outdoor landmark recognition system for the navigation of a mobile robot

Outdoor mobile robots usually rely on visual landmarks for guidance and navigation purposes. However the task of locating these landmarks in cluttered environment is very complex. The perceived size of the landmarks is a function of the imaging distance of the robot. Also, the appearance of the landmark may vary due to changes in lighting, viewing direction and interfering objects. In this paper we present a fractal based approach to landmark detection. Fractals are inherently scale invariant; the model presented here is also invariant to changes in light intensity. We present the performance of the incremental fractional Brownian motion (IFBM) classifier for natural textures as well as a segmentation tool for natural scene images