piratefsh

totally. while OpenCV is really useful and magical (i did learn a lot of theory from the OpenCV tutorials though), it didn't help me wrap my head around concepts, but implementing the algorithms (gaussian blur, edge detection, etc) without having fully grasped the math helped a whole lot with understanding how things work. i still can't explain the math behind edge detection, for example, but i can describe how it works. when i wrote this, i had in mind a person who would like to get a big picture idea of what image processing is, and will hopefully be inspired to learn what happens under the hood.

yes! i've found it really useful when dealing with images of items in different lighting conditions. i've struggled with understanding histogram equalization, would you happen to have good resources that explain how it is done?

i totally agree that the fun part lies in understanding how things work under the hood. i never understood how edge detection work until i worked on an implementation with JavaScript and canvas, and that was a fantastic learning experience. the motivation behind this article was to provide a general idea of what image processing could do, and hopefully encourage someone to delve deeper into the mechanics of image processing :)

ahh this is great! opencv tutorials with detailed explanations on the algorithms are hard to come by. i've found tutorials really useful to learn some of the standard processes in image processing (i.e. grayscale and blurring to remove noise).