Self Organizing and Fuzzy Modelling for Parked Vehicles Detection

Our aim is to distinguish moving and stopped objects in digital image sequences taken from stationary cameras by a model based approach. A self-organizing model is adopted both for the scene background and for the scene foreground, that can handle scenes containing moving backgrounds or gradual illumination variations, helping in distinguishing between moving and stopped foreground regions. The model is enriched by spatial coherence to enhance robustness against false detections and fuzzy modelling to deal with decision problems typically arising when crisp settings are involved. We show through experimental results and comparisons that good accuracy values can be reached for color video sequences that represent typical situations critical for vehicles stopped in no parking areas.