Outdoor Landmark Recognition Using Hybrid Fractal Vision System and Neural Networks

Landmarks are useful cues for autonomous mobile robot navigation. Due to the changing imaging conditions, the appearance of the landmarks is varying in outdoor environments. We will develop a novel system to detect and recognize the landmarks. The developed system will be able to overcome changes in scale, lighting, etc. The proposed approach is based on a two-step method, using both fractal based object classifier and neural network based object identifier. Since fractals are inherently scale invariant over a finite range of scales, they make good models for outdoor scene objects. Since neural networks have fast recognition capabilities, they are a good choice in real time mobile robot applications.