Outdoor Landmark Recognition Using Hybrid Fractal Vision System and Neural Networks
NORTH CAROLINA STATE UNIV AT RALEIGH
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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.
- Land and Riverine Navigation and Guidance