This project implements a real-time number plate recognition system using OpenCV and Tesseract OCR. The system captures video from a camera, detects number plates in the frames, and extracts the text from those plates.
- Real-time number plate detection and recognition.
- Efficient preprocessing steps to improve OCR accuracy.
- Saves recognized number plates to an Excel file.
- Python 3.x
- OpenCV
- NumPy
- Pandas
- Pillow
- Pytesseract
- Tesseract OCR
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Clone the repository:
git clone https://github.com/karthick-V-212223040086/RealTime-Plate-Recognition.git cd number-plate-recognition -
Install the required packages:
pip install opencv-python numpy pandas Pillow pytesseract
Download and install Tesseract from here.
Set the Tesseract executable path in the script if necessary (uncomment the line in the code).
Run the script:
python number_plate_recognition.py
The camera feed will start, and the system will begin recognizing number plates. Press 'q' to quit the application.
Recognized number plates will be saved to an Excel file named `recognized_number_plates.xlsx` in the current directory.
## Code Explanation
The main components of the script are:
- **Number Plate Detection**: Using contour detection and morphological operations to identify and isolate potential number plates.
- **Image Preprocessing**: Techniques such as Gaussian blur and adaptive thresholding are used to enhance the image for better OCR results.
- **OCR Processing**: Pytesseract is employed to recognize text from the processed images of number plates.
- **Results Handling**: The script avoids duplicate entries and saves recognized plates in an Excel file.
## Contributing
Feel free to contribute by submitting issues, feature requests, or pull requests!
-- if you have any quires feel free.. if you have blocked accound no probelm ill create my own pull request too
## Acknowledgements
- OpenCV
- Tesseract OCR