Road vehicle detection using fuzzy logic rule-based method

Road vehicle detection using very high-resolution remote sensing images has a unique advantage of covering a large area at the same time over all ground-based detectors. But the detection of small vehicle-object in remote sensing imagery is still a challenging task. A scheme was proposed to detect road vehicle objects from airborne color digital orthoimagery based on fuzzy logic rule base. Firstly, a vector-generated road mask was used to constrain detection of vehicles to road region. Secondly, image segmentation algorithm was performed to form image objects in the preprocessing orthoimagery. Finally, based on a set of fuzzy logic rules defined by membership functions, vehicle objects were detected and separated from other objects. A representative set of road segment images was selected from available images to test the proposed scheme. Experimental results indicate that the detection rates of all test road-segments are high with very few false alarms.