VNPDR Employed in the Computer Vision Realm for Vehicle Authentication and Parking

License plate identification is necessary for a variety of applications, including automated toll collection, traffic law enforcement, security monitoring of restricted locations, and unattended parking lots (LPR). Due to different operating conditions, LPR procedures vary depending on the application. Permission for the vehicle to access the premises is definitely necessary in several public sectors, including hospitals, airports, schools and universities. Hospitals, community centers, and other public venues have limits on where vehicles are allowed to park. Parking the vehicles in specified spots, matters a lot in public areas in various circumstances. In hospitals, patients' lives are more important and emergency situations must be taken into mind. In university and collages the number of the vehicles usage and intake is more. The allotting the slots to them during the peak hour and authorizing the vehicle is very much difficult and it is tedious job. Automated license plate detection can help stop these incidents from happening by allowing us to focus on parking the vehicle while simultaneously checking that it is authentic. The suggested model begins by segmenting the image, then identifies and categorizes the vehicle. The parking space will be assigned to the specific vehicle based on the categorization. A multimodal approach is applied to detect and categorize the VNP images. The results and the accuracy of the multimodal approach are discussed.