How to find the best parameters to iris recognition?

Hello! I know the title says specifically for Iris isolation, but I've been struggling with this in general in my Image Processing class. To give some context I'll explain the assignment I'm working on and I hope to clear things up.

The problem is pretty simple: given a dataset (of roughly 30 images) of eyes, only one eye but it could be either a left or right eyes, I need to isolate the irises of said dataset. I need to remove the pupils and remove everything else that is not an iris from the image.

To remove the pupil what I do is:

• convert the image to greyscale
• apply gaussian blur
• apply thresholding (here i use a low lower threshold value around 30)
• apply hough transformation to find circles (cv2.HoughCircles)

To find the iris I do basically the same, but instead of thresholding i use Canny edge detection and apply the blur after the Canny.

As you can notices pretty much all of the steps have multiple arguments that you can pass to make the detection more accurats. My question is: how do I know what the best arguments are? So far I've spent a lot of time playing around with those and managed to make the isolation work for around half of the dataset. It can't be a process that manual to find the best parameter, right? Also to run for all the dataset it takes well over 1 minute and I have no idea how to test if the results are correct because. Am I supposed to iterate through multiple arguments combinations and pick them by hand?

I explained the problems I'm facing with this one assignment, but this has been a recurring issue whenever I work in an assignment from this class. I hope someone is willing to help me because i feel really stuck and frustrated with this class