|
Abstract:
|
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/suspect vehicles.
However, the traditional process of comparing those license plates utilizing
the matching of alphabet character is not effective. In traditional
methods, the system unable to detect the criminal/suspect vehicles if
the characters of the licence plate do not totally match with the blacklisted
license plates. This paper proposes the use of reputation algorithm
to detect the criminal/suspect vehicles that crossing the checkpoint
which license plates match with the blacklist in the checkpoint
database. In addition, we also use association analysis concept to detect
the vehicles crossing the checkpoint that might relate to the criminal
activity records. Our method can detect the suspect vehicles with
forged license plate by using color, brand and type of the vehicles instead
of only the license plate number matching method. 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. From our
extensive experiments, the results show that the reputation algorithm
and the association analysis concept can improve the detection capability
of the suspect vehicle detection system. |