The Automatic Number Plate Recognition (ANPR) system is a Python-based application that employs OpenCV for locating and recognizing license plates in images.

This repository is currently in an incomplete state.While it provides a basic implementation of the ANPR system, there are several planned enhancements and features that are yet to be implemented. I'll be adding further files soon.

The ANPR system is divided into two main components:

• Plate Localization:

  • This component identifies potential license plates within an input image using image preprocessing techniques and contour analysis.

• Character Segmentation and Recognition:

  • This component extracts individual characters from the identified license plates and utilizes OCR (Optical Character Recognition) to recognize the characters.

• Python 3.x
• OpenCV library
• Tesseract OCR engine
• pytesseract library

1. Install Python dependencies:

   pip install opencv-python-headless pytesseract pillow
   

2. Install Tesseract OCR:

   • Ubuntu:

     sudo apt-get install tesseract-ocr
     

   • Other Platforms:

     • Refer to the official installation guide.

1. Place the input images in the input_images directory.

2. Run the ANPR system:

   python anpr_system.py
   

   • The system will process each image in the input_images directory.
   • Detected plates and recognized characters will be displayed.

• To adjust preprocessing techniques or algorithms, modify the following functions in anpr_system.py:

  • localize_plate: Customize the plate localization algorithm.
  • segment_characters: Adjust character segmentation techniques.

• For training a custom OCR model, refer to the Tesseract documentation.

This project is licensed under the MIT License - see the LICENSE file for details.

• This project is based on the OpenCV and Tesseract OCR libraries, which are open-source and widely used in the computer vision community.