In Chapter 6, Image Processing in OpenCV, we learned about image processing mostly in terms of the image content and pixels. We learned how to filter them, transform them, or play around with the pixel values in one way or another. Even to match a template, we simply used the raw pixel contents to get a result and find out if an object exists in part of an image or not. However, we still haven't learned about the algorithms that allow us to differentiate between objects of a different kind, not just based on their raw pixels, but also the collective meaning of an image based on its specific features. It is almost a trivial task for a human being to identify and recognize different types of faces, cars, written words, and almost any visible and visual object, given that they are not extremely similar. For us human beings, this happens in most cases...
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