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ANPR - Automatic number plate recognition

Identify a vehicle license plate using image processing.

The chalenge is identify which region of the image is the plate and after apply an ocr over this region.

The purpose of this sample is not explain how to implement an OCR but how to find the plate for a given image.

Steps to achieve the goal

  1. Load the image and convert to grey scale

  2. Apply a gaussian filter to remove noise

  3. Apply more filters to transform to B&W and remove dark spots

  4. Find the edges of relevant regions of the image

  5. Apply OCR over these regions and get the plate number and get a collection of text.

  6. Iterate over this collection of text to check if this is a car plate or other info like a sticker, advertising or other text in some region of the image.

If you are working with fixed camera you can also check the position (x,y) of each region and avoid unecessary OCR processing since usually the plate is located in the same position in all vehicles.

What you need

  • python 2.7 ~ 3.x (used v 3.7.6)
  • some python libs (see bellow)

Install python libs

pip3 install sklearn
pip3 install matplotlib

Run

% python3 anpr.py

Expected Result

Original Image

img1

Image converted to greyscale

img2

Noise reduction

img3

Remove small dark spots and connect small bright cracks

img4

Clear objects connected to the label image border

img5

Cropped regions

result1

result2

and...

The Plate !

result3

Testing with OCR

After pushing the image plate region to this free OCR https://www.newocr.com/ received the text: MUIEPSD - \o/

result3

Other techniques

You can try other filters or adjust the parameters to achieve a better accuracy and performance.

other1

other2

other3

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