CODEWITHSUNDEEP
pythonopencvcomputer-vision
iamoracle
iamoracle

Reputation: 96

How to use openCV to change white to black?

I have a bean on a white background damper, the issue is that the damper is not perfectly white (as in 255,255,255). I have tried using cv2.threshold() method but I kept getting a deformed image with spots. What is the best way to achieve this?

My Image

enter image description here

My Code

gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)

ret, thresh = cv2.threshold(gray, 240, 255, cv2.THRESH_BINARY)

img[thresh == 255] = 0

kernel = cv2.getStructuringElement(cv2.MORPH_ELLIPSE, (5, 5))
erosion = cv2.erode(img, kernel, iterations = 1)

cv2.namedWindow('image', cv2.WINDOW_NORMAL)
cv2.imshow("image", erosion)

In the end, the beans should only be surrounded by black images!

Upvotes: 2

Views: 860

Answers (1)

crackanddie
crackanddie

Reputation: 708

It could be the solution:

import cv2
import numpy as np


img = cv2.imread("data/bob.jpg")
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)

img_blured = cv2.blur(gray, (5, 5))
ret, thres = cv2.threshold(img_blured, 130, 255, cv2.THRESH_BINARY)

neg = cv2.bitwise_not(thres)
erosion = cv2.erode(neg, np.ones((6, 6), np.uint8), iterations=1)
cv2.imshow("erosion", erosion)

# ret, thresh = cv2.threshold(gray, 240, 255, cv2.THRESH_BINARY)
img[erosion == 0] = 0

cv2.imshow("image", img)
cv2.waitKey(0)

Here I am using cv2.threshold but for bigger range than you used, but before it I blured the image. Then I negate and erode it.
But this cuts off the bean itself a little, if this is critical, then you should use a completely different algorithm. For example, the cv2.Canny method to find the contours of a bean and somehow further process it.

Upvotes: 4

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