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As the title suggest, i want to build an ANPR application in windows. I am using Brazilian number plates. And i am using OpenCV for this.

So far i manged to extract the letters form the numberplate. Following images show some of the numbers i have extracted.

enter image description here enter image description here enter image description here The problem i am facing is that how to recognize those letter. I tried to use Google tesseract. But it fails to recognize them sometimes. Then i tried to train an OCR data base using OpenCV i used about 10 images for each character. but it also did not work properly.

So i am stuck here. i need this for final year project.So can anybody help me?? i would really appreciate it.

Following site does it very nicely https://www.anpronline.net/demo.html

Thank you..

user2389323
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  • You had better add some details on what you tried, preferably with code, and clearly say what "it also did not work properly" means. Otherwise someone will flag your question as off-topic (given the down-vote, that has probably already happened) – Bull Nov 20 '13 at 14:30

2 Answers2

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you could train an ann or multi-class svm on the letter images, like here

berak
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  • NN or SVM will work, but 10 training images for each character is not going to be enough. For SVM you need a validation set to for choosing parameters. How much data is needed depends on the quality of images and and the variabilty of digits. But it should be reasonably easy to make a decent sized set. – Bull Nov 20 '13 at 14:27
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Check out OpenALPR (http://www.openalpr.com). It already has the problem solved.

If you need to do it yourself, you really do need to train Tesseract. It will give you the best results. 10 images per character is not enough, you need dozens or hundreds. If you can find a font that is similar to your plate characters, a good approach is to print out a sheet of paper with all of the characters used multiple times. Then take 5-10 pictures of the page with your camera. These can then be your input for training Tesseract.

Derrick Johnson
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