Applying fuzzy logic in video surveillance systems

In this work, the application of fuzzy logic in surveillance systems based on cameras is Analyzed. Three different fuzzy systems have been tested and compared with a crisp decision system. The first one has been developed using an expert knowledge, the second one was learned from recorded videos, and a third one is developed as a refinement taking into account evaluation with ground truth. In all cases, the core of the system is the association function, in which the developed fuzzy system takes decision about what blobs (detected pixels grouped in a zone) belong to what tracks. In this work the surveillance video system is deployed in an airport. It is embedded in an A-SMGCS Surveillance function for airport surface, based on video data processing, in charge of the automatic detection, identification and tracking of all interesting targets (aircraft and relevant ground vehicles). The system evaluation has been developed using an evaluation function specifically designed for this type of problem. Results obtained with real data in representative ground operations show different capabilities for each system to solve complex scenarios and to improve tracking accuracy.