Detecting Vehicle Type and License Plate Number of different Vehicles on Images

TL;DR

This paper presents a system combining Mask R-CNN, WpodNet, and pytesseract to detect vehicle types and recognize license plates in images, aiding urban vehicular tracking and management.

Contribution

It introduces an integrated model that simultaneously detects vehicle types and reads license plates using deep learning and OCR techniques.

Findings

Accurate vehicle type detection in diverse images

Effective license plate recognition with high precision

Potential for real-time urban vehicle tracking

Abstract

With ever increasing number of vehicles, vehicular tracking is one of the major challenges faced by urban areas. In this paper we try to develop a model that can locate a particular vehicle that the user is looking for depending on two factors 1. the Type of vehicle and the 2. License plate number of the car. The proposed system uses a unique mixture consisting of Mask R-CNN model for vehicle type detection, WpodNet and pytesseract for License Plate detection and Prediction of letters in it.