Suspect Vehicle Detection Using Vehicle Reputation with Association Analysis Concept

The suspect vehicle detection system normally compares the list of criminal license plates and vehicle license plates gathering from various sensors in order to identify the criminal vehicles or the suspect vehicles. However, the traditional process of comparing those license plates utilizing the matching of alphabet character is not effective. If the characters do not match any one character, the system can not detect the criminal vehicles or the suspect vehicles. This paper proposes the use of reputation algorithm to detect the criminal vehicles crossing the checkpoint whose license plates match the blacklist. In addition to that, we use association analysis concept to detect the suspect vehicles that have ever passed the checkpoint that may be related to the criminal activity records. Our method can detect the suspect vehicles with fake license plate by using color, brand and type of the vehicles instead of only the license plate matching to the blacklists. These two techniques use a blacklist of criminal vehicles and criminal activity recorded in a criminal report database of Defence Technology Institute (DTI), Thailand, to help facilitate the detection process. The result shows that the reputation algorithm and the association analysis concept can improve the detection capability of the suspect vehicle detection system.