  Over the last decade, there has been a spike in criminal activity all around
the globe. According to the Indian police department, vehicle theft is one of
the least solved offenses, and almost 19% of all recorded cases are related to
motor vehicle theft. To overcome these adversaries, we propose a real-time
vehicle surveillance system, which detects and tracks the suspect vehicle using
the CCTV video feed. The proposed system extracts various attributes of the
vehicle such as Make, Model, Color, License plate number, and type of the
license plate. Various image processing and deep learning algorithms are
employed to meet the objectives of the proposed system. The extracted features
can be used as evidence to report violations of law. Although the system uses
more parameters, it is still able to make real time predictions with minimal
latency and accuracy loss.
