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I'm working on my project for License Plate Recognition using OpenCV & Tesseract. I use OpenCV to change original image to processed image so that Tesseract can read it well. For example)

Original Image enter image description here

Processed Image enter image description here

But the result shows "38다9502"and it recognized 3 to 5. These situation happens frequently especially when the number is 3 or 5. Is there any suggestion or solution for it??

iraj jelodari
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Jagpaw
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3 Answers3

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You can try retraining tesseract with some of your own data. It looks like a good candidate for simply fine-tuning the model. You may not even need much data, just give it several examples of the digits it is having trouble with.

Instructions for retraining are here: https://github.com/tesseract-ocr/tesseract/wiki/TrainingTesseract-4.00

shortcipher3
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1)First it can be done with few image processing techniques which is mentioned in this link(https://cvisiondemy.com/license-plate-detection-with-opencv-and-python/)

2)Next if it doesn't show any improvement you can try image thresholding which you can go through in this link(https://docs.opencv.org/master/d7/d4d/tutorial_py_thresholding.html)

3)If above steps didn't work ,then try to enlarge your image size.

JananiC_Intel
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I solved this question with using multiple models supported by Tesseract. With Hangul model, I only received accurate information of Hangul word, not Numbers. However, with English model, I can received accurate information of Numbers. So I used these models in parallel and it resulted 99% accuracy of LPR.

Jagpaw
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