How to find the center of black objects in an image with python opencv?

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I have a problem finding the contours of black objects on white background.

example

here I added an example of an image. Now I need to find center of black regions and I use following code.

im = cv2.imread(img)
plt.imshow(im)
gray = cv2.cvtColor(im, cv2.COLOR_BGR2GRAY)
blurred = cv2.GaussianBlur(gray, (5, 5), 0)
thresh = cv2.threshold(im, 60, 255, cv2.THRESH_BINARY_INV)
cnts = cv2.findContours(thresh, cv2.RETR_EXTERNAL,cv2.CHAIN_APPROX_SIMPLE)
cnts = imutils.grab_contours(cnts)

However it gives an error like

TypeError: Expected Ptr for argument 'image' " for the image argument of cv2.findeContours().

How can I solve this? or if you have any other idea how to find center of black regions I would like to hear. Thanks.

computer-vision opencv image-processing image python
1 Answers

You're on the right track. When you perform find contours on your image, OpenCV expects that the foreground objects to detect are in white with the background in black. To do this, you can Otsu's threshold with the cv2.THRESH_BINARY_INV parameter to get the objects in white. From here we can find contours and find the center of each region by calculating for the centroid with cv2.moments. Here's the results:

Binary image

enter image description here

Center of object drawn in blue with the bounding box in green. You can get the coordinates of each contour by checking the cX and cY variables.

enter image description here

You can crop each individual ROI using Numpy slicing then save with cv2.imwrite

enter image description here

Code

import cv2
import numpy as np

# Load image, grayscale, Gaussian blur, Otsu's threshold
image = cv2.imread('1.png')
original = image.copy()
gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
blur = cv2.GaussianBlur(gray, (3,3), 0)
thresh = cv2.threshold(blur, 0, 255, cv2.THRESH_BINARY_INV + cv2.THRESH_OTSU)[1]

# Find contours
ROI_number = 0
cnts = cv2.findContours(thresh, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
cnts = cnts[0] if len(cnts) == 2 else cnts[1]
for c in cnts:
    # Obtain bounding rectangle to get measurements
    x,y,w,h = cv2.boundingRect(c)

    # Find centroid
    M = cv2.moments(c)
    cX = int(M["m10"] / M["m00"])
    cY = int(M["m01"] / M["m00"])

    # Crop and save ROI
    ROI = original[y:y+h, x:x+w]
    cv2.imwrite('ROI_{}.png'.format(ROI_number), ROI)
    ROI_number += 1

    # Draw the contour and center of the shape on the image
    cv2.rectangle(image,(x,y),(x+w,y+h),(36,255,12), 4)
    cv2.circle(image, (cX, cY), 10, (320, 159, 22), -1) 

cv2.imwrite('image.png', image)
cv2.imwrite('thresh.png', thresh)
cv2.waitKey()
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