Hi Spears,
thank you for your answer. I have tried so far only Tesseract and Microsoft ocr but it was not good enough, I need 100% accuracy. I have binaryse image, scale but it didn't help.
I haven't use neural networks yet, because that is much more effort than standard comparing of image pixels. It looks like that ipoker displays limited number of different fonts for digits, so I am solving the problem by finding all of different digits they display, save those digits as templates and compare unseen digit to saved black and white templates. So far I read everything 100% accurate except bot stack, I guess that I still didn't find all different digits for bot stack which ipoker displays. I parse player names from xml file which ipoker saves at the start of each hand in DataTemp folder, which saves a lot of work. My idea was to first try approach of converting image to black and white and save all templates of digits I find, which works fine so far and if it doesn't work to try to use neural networks. I was working on recognizing hand written digits using neural network during my phd, but there the database is large, there are many test samples, for ipoker I can provide to neural network only few samples for each digit, which would likely result in overfitting (learning by heart).
I have attached 3 different samples of digit 3 I have found so far for bot stack (bot stack differs from other stacks). It would be easy if I would know, there are 3 different font sizes ipoker uses to display digits, but I don't know how many different, I can only let bot play and throw exception if he doesn't read e.g. stack properly so I can cut the unseen digits and save it to templates, and do that until bot reads everything properly.
| Attachments: |
 sample3.PNG [ 248 Bytes | Viewed 11624 times ] |
 sample2.PNG [ 248 Bytes | Viewed 11624 times ] |
 sample1.PNG [ 252 Bytes | Viewed 11624 times ] |