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Best approach to detect read numbers from 1 to 99

asked 2017-05-15 14:40:15 -0500

Damien45 gravatar image

Hi !

I'm currently using OpenCV to detect things on a video and those things have sometime a number printed on, which I want to read. Theses numbers could be from 1 to 99 and I'm able to extract them in a binary image as :

http://vps166675.ovh.net/img126.jpg.b... http://vps166675.ovh.net/img130.jpg.b... http://vps166675.ovh.net/img101.jpg.b...

I try these approches : - Cascade classification using HAAR and HOG classifier : very poor results even if I work with ~500 positives images and thousands of negatives (I train these classifier using gray-scale images) - Tesseract OCR, but, even with these binary images, and even if I told him that there is only digits, it reads 3 as many as 8, so it is not reliable (And it actually reads nothing most of the time).

Have you any advice to handle these case ? Maybe a feature type that I don't try ? A hack using hough line detection or things like that ?

Thank you in advance.

Damien.

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answered 2017-05-24 14:10:01 -0500

Tesserat is best in ocr. The hack is make the ROI size height 20 pixel x 40 pixel. Use pyup or pydown for image.

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Asked: 2017-05-15 14:40:15 -0500

Seen: 331 times

Last updated: May 15 '17