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License Plate Recognition using OpenCV Python (Assignment Sample)
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by Keshav Rowjee
cvbpr1
CSE 3093Y Assignment March 2021
License Plate Detection
1. The image is rescaled to a suitable size and then it is greyscaled.
2. With a bilateral filter, details that are not desired is filtered out.
3. Next canny edge detection is performed.
4. Contours are sought on the image. The first 10 contours found are arranged from biggest to smallest. The results are checked; which of them is a rectangle shape contour with four sides and closed figure. The contour matching has a red rectangle drawn around it.
5. The other parts, other than where the ‘numbers’ are, are on the plate are masked.
2. Character Segmentation
The licence plate is cropped, greyed and saved as a new image.
3. Character Recognition
Pytesseract is used to extract information on the plate, that is reading the characters on the plate. The detected license plate number is displayed.
cvbpr1
CSE 3093Y Assignment March 2021
License Plate Detection
1. The image is rescaled to a suitable size and then it is greyscaled.
2. With a bilateral filter, details that are not desired is filtered out.
3. Next canny edge detection is performed.
4. Contours are sought on the image. The first 10 contours found are arranged from biggest to smallest. The results are checked; which of them is a rectangle shape contour with four sides and closed figure. The contour matching has a red rectangle drawn around it.
5. The other parts, other than where the ‘numbers’ are, are on the plate are masked.
2. Character Segmentation
The licence plate is cropped, greyed and saved as a new image.
3. Character Recognition
Pytesseract is used to extract information on the plate, that is reading the characters on the plate. The detected license plate number is displayed.
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