How to normalize position of the elements on the picture [OpenCV]

Question

I am currently working on program which could help at my work. I'm trying to use Machine Learning for the classification purpose. The problem is that I don't have enough samples for training the model and augmentation is something I'm trying to avoid because hardware problems (not enough RAM) either on my company laptop and on the Google Collab. So I decided to try to somehow normalize the position of the elements so the differences would be visible for the machine even with no big amount of different samples. Unfortunately now I'm struggling how to normalize those pictures.

Element 1a:

Element 1b:

Element 2a:

Element 2b:

Elements 1a and 1b are the same type and 2a - 2b are the same type. Is there a way to somehow normalize position for those pictures (something like position 0) which would help the algorithm to see differences between them? I've tried using cv2.minAreaSquare to get the square position, rotating them and cropping don't needed area but unfortunately those elements can have different width so after scaling them down the contours are deformed unevenly. Then I was trying to get symmetry axis and using this to do a proper cropping after rotation but still the results didn't meet my expectations. I was thinking to add more normalization points like this:

Normalization Points:

And using this points normalize position of the rest of my elements but Perspective Transform takes only 4 points and with 4 points its also not very good methodology. Maybe you guys know a way how to move those elements to have them in the same positions.

user_1196549 · Answer

Seeing the images, I believe that the transformation between two pictures is either an isometry (translation + rotation) or a similarity (translation + rotation + scaling). These can be determined with just two points. (Perspective takes four points but I think that this is overkill.)

But for good accuracy, you must make sure that the points are found reliably and precisely. In the first place, you need to guess which features of the shapes are repeatable from one sample to the next.

For example, you might estimate that the straight edges are always in the same relative position. In such a case, I would recommend finding two points on some edges, drawing a line between them and find intersections between the lines.

In the illustration, you find edge points along the red profiles, and from them you draw the green lines. They intersect in the yellow points.

For increased accuracy, you can use a least-squares approach to find a best fit on more than two points.

How to normalize position of the elements on the picture [OpenCV]

1 Answers