Vehicle Identification and Surveillance Using Efficient Machine Learning Techniques

Identification of vehicles is an important area of research. It has several applications namely toll gate fee management systems, automatic parking applications, theft prevention, traffic monitoring and ticket(fine) imposing etc. Presently, there are many vehicles manufacturers marketing various types of vehicles, and this has an increasing growth rate. It has become a difficult task to analyze various attributes of vehicles and to identify each one of them. Vehicle identification is the main objective of this project. Using license plate, different vehicles can be identified but it is troublesome when the license plate recognition fails in scenarios where the license plate is forged, missing, or covered. The attributes such as the model and make of the vehicle cannot be easily changed and this helps in recognition of vehicles easily. In this project, vehicle recognition mainly focuses on identifying the name of the vehicle manufacturing company. Further recognition is done by the extraction of the license plate number by employing Haar Cascade classifier.