License Plate Recognition with OpenCV and Tesseract OCR

License Plate Recognition (LPR) is a powerful tool in computer vision, used in applications like automated toll collection, traffic monitoring, and security surveillance. This blog post will walk you through building an LPR system using Python, OpenCV, and Tesseract OCR. Don’t worry if you’re new to these technologies; each step is broken down to ensure clarity and ease of understanding.

Prerequisites

To follow along with this tutorial, you’ll need basic Python knowledge. You’ll install necessary libraries, work with image processing using OpenCV, and use Tesseract OCR to extract text from the images.

Required Libraries

pip install opencv-python-headless opencv-python opencv-contrib-python pytesseract ipywidgets matplotlib seaborn

Project Overview

We’ll be using OpenCV to process images of license plates, detect the license plate region, and then extract text from it using Tesseract OCR. The project follows these main steps:

1. Load an image of a vehicle’s license plate.
2. Preprocess the image (grayscale conversion, blurring, edge detection).
3. Detect the license plate region.
4. Extract the text from the license plate using OCR.
5. Display results, including OCR accuracy metrics.

Step 1: Load and Display the License Plate Image

We start by loading an image from a URL using Python’s PIL and URL libraries, converting it to an array for OpenCV processing.

import cv2
import pytesseract
import numpy as np
import matplotlib.pyplot as plt
from urllib.request import urlopen
from PIL import Image
import ipywidgets as widgets
from IPython.display import display

# Load an image from a URL (replace with an appropriate dataset URL)
def load_image_from_url(url):
    response = urlopen(url)
    img = Image.open(response)
    img = np.array(img)
    return img

# URL for a sample license plate image (replace with an actual dataset URL)
img_url = 'https://upload.wikimedia.org/wikipedia/commons/1/14/FI_license_plate.jpg'
original_image = load_image_from_url(img_url)

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