Exercise 4 was rather a mix of easy and hard, unlike the other exercises. The exercise was all about binarization and edge detection. Binarization is a process of turning the photo foreground to black, then the background would be white, or vice versa, given a threshold. Edge Detection simply means detecting the edges or outlines of the foreground of the photo.
Now why did I thought it was a mix of easy and hard? That's because the difficulty of these two processes depends on the photo one is working with. For example, in the Binarization part, we found the quote.jpg and magazin1.jpg easier to binarize, while magazin2.jpg was harder to binarize. My partner and I used brute force to get rid of the annoying background so it would be easier to make the text appear.
Original quote.jpg.
Binarized quote.jpg where the the letters of the image are all in black.
Original magazin1.jpg.
Binarized magazin1.jpg.
Original magazin2.jpg.
Binarized magazin2.jpg. Notice how the photo is still not clean and still has the noise from the original photo.
As for the Edge Detection part, the photo was really hard to work on with, since one part looked illuminated while the other didn't. While I was able to (somehow) get the edges, the algorithm we did may not be correct as we still used brute force to binarize the photo.
Original source.png.
Binarized source.png.
While I understood the purpose of Binarization, I didn't appreciate the Edge Detection much, since it invloved a lot of steps compared to Binarization. I still understood the two concepts nonetheless. Hopefully I would get to appreciate Edge Detection when we get to the later exercises.
