Exercise #4 Binarization and Canny Edge Detection.

For this exercise.

First, we binarized a bunch of images.
The following images are used for binarization.

For this set of images, we set thresholds for themselves for better binarization. As using one code for all is not an easy task for this one, we opted to hardcode it, making it so that each image use their own bits of the code.

The following are the output.

Next, for Adaptive thresholding, we used this sample image.

For its algorithm, we used the mean of the neighbors of the pixel of interest. Using it, we got this binarized image.

For detecting edges, we used a blur function built in in OpenCV. We also used Sobel and Canny Edge Detectors that are built in on the images.

That is all.