I'm coding an Optical Character Recognition specifically for the Internet meme images. This is a school project and it should be coded in C.I'm currently having trouble with the method/algorithms I will use to code my OCR. Indeed, almost all meme images have the same font which is Impact (never mind for the others which haven't the Impact font). The OCR goal will be to detect and recognize characters, that are in the Impact font, in the foreground of the meme image and not in the behind scene of it.To do this OCR, I mean that a neural network is a bit overkill because the characters in the meme image are simple, straight and forward. I have heard that there are other more simply ways to do an OCR like use a machine learning algorithm to learn the Impact font or use a system based on skeleton matching to recognize characters by pattern recognition.What's the best way to do my OCR? Rather a neural network? A pattern recognition? Machine learning?
One font OCR for meme images
algorithms;c
You probably can brute-force recognition of most characters, once you've determined the bounding box, by rendering the most common characters over them (e.g. printable ASCII) and looking at the difference. I still suspect that a pretty simple neural network could do much faster if you'd feed it with relatively large blocks of the suspect letter (e.g. a 8 x 10 matrix, or even coarser), with any colorful content removed / replaced by one color, since meme letters are generally white with a black border. The network would need to be trained, though.