Ask Your Question
0

Best approach to detect read numbers from 1 to 99

asked 2017-05-15 14:40:15 -0600

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.

edit retag flag offensive close merge delete

Comments

1 answer

Sort by ยป oldest newest most voted
0

answered 2017-05-24 14:10:01 -0600

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

edit flag offensive delete link more

Question Tools

1 follower

Stats

Asked: 2017-05-15 14:40:15 -0600

Seen: 1,164 times

Last updated: May 15 '17