\nI’ve already mentioned about my first OCR attempt for my Draw Something Solver, and the disappointing results.\n<\/p>\n
\nI said the letters did not appear to be consistant, this turned out to be on my iPhone 4S, the spacing of the letters is not consistant, there are a few pixels difference between the letters on the left and those on the right. Once I had discovered this, the letters matched.\n<\/p>\n
\nHowever, taking this approach meant only images taken from a retina enabled iPhone would work, those from a lower resolution screen would not match. I would need to take screenshots of every letter on every device at every resolution to be consistant. Not a very good idea.\n<\/p>\n
\nMy next approach was to scale to image down to a common size using an HTML5 canvas, that didn’t produce consistant results. I tried to grayscale, and to turn to black and white, but although close, they were still too different.\n<\/p>\n
\nMy final approach, and one that seems to work for now is to still scale and turn the images to black and white, but instead of hashing this result, I am instead doing some pixel comparison and generating probabilities of matching a letter. This is a simple neural network. I have trained it with all the letters from my iPhone 4S so that runs consistantly each time. When I ran against images from an iPhone 3GS, not all images matched, letters like “I” and “J” caused confusion, so where a match was wrong I added some extra training data for those letters so they all now match. I have yet to try images from an iPad as I don’t have one, but I hope they will match first time without further training.\n<\/p><\/p>\n","protected":false},"excerpt":{"rendered":"