[dimatura]

You can examine the code of zxing-cpp (which is fairly nice IMO) for a simple, "classical computer vision" approach to this. It's not the most robust implementation but it is pretty functional.

But in general, you can divide the problem more or less like this (not necessarily in this order) 1. find the rough spatial region of the barcode. Crop that out and only focus on this 2. Correct ("rectify") for any rotation or perspective skew of the barcode, turn it into a frontoparallel version of the barcode 3. Binarize the image from RGB or grayscale into pure black and white 4. Normalize the size so that each pixel is the smallest spatial unit of the barcode.