Automatic Toll Tax Collection System
Web Based Toll Payment System with Python Backend
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Project Overview
- Objective: This project automated toll tax payments through a web-based frontend and Python backend that detects and recognizes vehicle number plates in real time at toll plazas.
- Tools & Technologies: Python 3.6, OpenCV, TensorFlow, Keras, HTML, Convolutional Neural Network (CNN)
Problem Statement
This system is designed to streamline toll tax payments by integrating a web-based frontend with a Python backend that detects and recognizes vehicle number plates as they pass through a toll plaza. The primary objective is to automate the toll collection process, reducing the need for manual intervention.
Key Features
- Automated detection and recognition of vehicle license plates using CNN and image processing.
- Real-time database updates for toll entry logging.
- Downsampled to 40 frames per video to reduce overfitting.
Outcome
The prototype system accurately recognized number plates and successfully logged toll entries into the database. The frontend interface provided a convenient way for users to check and pay their toll dues. The project highlighted the integration of machine learning, image processing, and web development to solve a real-world infrastructure challenge.
Reflection
The system accurately recognized vehicle number plates and recorded toll entries in the database. The web interface allowed users to view and pay toll charges. This project demonstrated the use of machine learning, image processing, and web development in addressing a practical transportation problem.