Camera based parking lot vehicle detection system with fuzzy c-means classifier

Abstract

This paper proposes to improve the performance of the camera-based vehicle detection system by using the classifier based on fuzzy c-means (FCM) clustering. For reducing computation, the semi-hard clustering approach is applied and the hyper-parameters are tuned by particle swarm optimization (PSO). The new system was introduced to an underground parking lot at Ginza, Tokyo in October 2009. The system was also tested at an outdoor (rooftop) parking lot for a period of two months and achieved the detection rate (sensitivity) of 99.6%. The performance clearly surpassed the initial goal of the project.