如何在二进制图像中找到特定点？

Question

I'm starting a research at the university, with the theme of enabling the use of AI to calculate a region of the retina. The first part we stipulated was to segment two important parts of the retina, using u-net. The second is to use the result of segmentation to find the important points and perform a calculation.

So, in the below image, I show the output of segmentation each region, using u-net (The red annotation isn't part of segmentation). I tried represent regions that I want find in first and second block. Once did, I could calculate distance between these points, when merge them. So, my question is: what kind of technique I can use to read the pixels in order of to find the coordinates where I marked?

Is OpenCV a lib that could help me? It's the first time that I handle with this kind of problem, so thanks for any suggestion or guidance.

Answer 1

Using OpenCV: detecting the margins can be done with connectedComponentsWithStats() method.

connectivity = 8  
output = cv2.connectedComponentsWithStats(binary_img, connectivity, cv2.CV_32S)

stats = output[2]         # stat matrix

first_blob_left = stats[0,cv2.CC_STAT_LEFT]
first_blob_right = stats[0,cv2.CC_STAT_RIGHT]
second_blob_left = stats[1,cv2.CC_STAT_LEFT]
second_blob_right = stats[1,cv2.CC_STAT_RIGHT]

if first_blob_left < second_blob_left:
    dist = second_blob_left - first_blob_right
else:
    dist = first_blob_left - second_blob_right

detecting the deepest point can be done with the same method:

connectivity = 8  
output = cv2.connectedComponentsWithStats(binary_img, connectivity, cv2.CV_32S)

stats = output[2]         # stat matrix

blob_top = stats[0,cv2.CC_STAT_TOP]
blob_height = stats[0,cv2.CC_STAT_HEIGHT]

deepest_point_y_position = blob_top + blob_height

Note: This code hasn't been tested, it may contains some typos. But still, the idea stays the same, and should work without much effort.

Take a look at

labels = output[1]

"labels" is an array the site of the input image, where each pixel of a blob is labelled with the same value. This should help you to find the coordinates of the margins