Python - How to detect hard edges of multiple thumbnails and save the coordinates?

Question

We have a scanned white page - A4 size that contains multiple thumbnails. The thumbnails are similar but not exactly the same. The thumbnails can be in random order and not in a very clear rows and columns. They are not totally random but they are in rows, however these are not a very accurate rows.

1. A4 page background color is white.

2. All thumbnails have black border of 5px and border-radius of 10 px Everyone of the thumbnails contains a green circle (Could be in the center or somewhere close to that).

   1. How can we detect the Hard Edges of every thumbnail and store the coordinates so we can crop the thumbnails for later processing and analyzing colors?

   2. How can we detect the circle in the center. We want to analyze and get all pixels RGB values contained into this circle and then calculate average RGB value.

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Update

This is the image:

Thank you

Answer 1

Main idea: As there are enough blank between the regions, so just crop each region by contours. Then for each region, use houghCircle to detect the circle in it.

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Your image is this:

After find external contours and calculate the bounding boxes:

For each contour, crop and find hough circle in it.

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Notice: I'll not provide my code for this question.

But post some links maybe useful for you. Learn and do by yourself:

1. Copy shape to blank canvas (OpenCV, Python)
2. cv2.drawContours() - unfill circles inside characters (Python, OpenCV)
3. How to detect colored patches in an image using OpenCV?
4. Edge detection on colored background using OpenCV
5. How can I get the minimum enclosing circle with OPENCV?
6. How can I prepare circle path text image for OCR program?

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Update:

To detect the circle, you should select the right parameters, depends on your source image.

Try! Try! TRY!

Here is the circle detection I tried:

circles = cv2.HoughCircles(gray, cv2.HOUGH_GRADIENT,
                    dp=1, minDist=20, circles=None,
                    param1=200 , param2=50,
                    minRadius=120, maxRadius=150
                )