In this tutorial, you will build a basic Automatic License/Number Plate Recognition (ANPR) system using OpenCV and Python.

ANPR is one of the most requested topics here on the PyImageSearch blog.

I’ve covered it in detail inside the PyImageSearch Gurus course, and this blog post also appears as a chapter in my upcoming Optical Character Recognition book. If you enjoy the tutorial, you should definitely take a look at the book for more OCR educational content and case studies!

Automatic License/Number Plate Recognition systems come in all shapes and sizes:

• ANPR performed in controlled lighting conditions with predictable license plate types can use basic image processing techniques.
• More advanced ANPR systems utilize dedicated object detectors, such as HOG + Linear SVM, Faster R-CNN, SSDs, and YOLO, to localize license plates in images.
• State-of-the-art ANPR software utilizes Recurrent Neural Networks (RNNs) and Long Short-Term Memory networks (LSTMs) to aid in better OCR’ing of the text from the license plates themselves.
• And even more advanced ANPR systems use specialized neural network architectures to pre-process and clean images before they are OCR’d, thereby improving ANPR accuracy.

#python