How to remove the background from a picture in OpenCV python - python-3.x

Question

Because I am new to computer vision. I would like also to ask how can I delete the whole background of this image and keep only the pills untouched. I tried different things like to change the background color but still, there are some small edges and also noise.
Or if it's possible for all the white background to be a neutral color, without the line between the circle.

Answer 1

Here is one way in Python/OpenCV. Threshold the image on white. Then apply some morphology to clean it up a bit. Then invert it to make a mask. Then apply the mask to the input. I note that your pills overlap the ring. So this method does not remove the ring.
Input:
import cv2
import numpy as np
# Read image
img = cv2.imread('pills.jpg')
hh, ww = img.shape[:2]
# threshold on white
# Define lower and uppper limits
lower = np.array([200, 200, 200])
upper = np.array([255, 255, 255])
# Create mask to only select black
thresh = cv2.inRange(img, lower, upper)
# apply morphology
kernel = cv2.getStructuringElement(cv2.MORPH_ELLIPSE, (20,20))
morph = cv2.morphologyEx(thresh, cv2.MORPH_CLOSE, kernel)
# invert morp image
mask = 255 - morph
# apply mask to image
result = cv2.bitwise_and(img, img, mask=mask)
# save results
cv2.imwrite('pills_thresh.jpg', thresh)
cv2.imwrite('pills_morph.jpg', morph)
cv2.imwrite('pills_mask.jpg', mask)
cv2.imwrite('pills_result.jpg', result)
cv2.imshow('thresh', thresh)
cv2.imshow('morph', morph)
cv2.imshow('mask', mask)
cv2.imshow('result', result)
cv2.waitKey(0)
cv2.destroyAllWindows()
Threshold image:
Morphology cleaned image:
Mask image:
Result:

Answer 2

Here is another way to do that in Python/OpenCV removing the ring. But it will remove parts of the pills that overlap the ring.
Read the input
Threshold on white
Apply morphology close to remove the center strip
Get the contours
Draw the contours as white filled on black background
Get the convex hull of the white filled contours
Fit an ellipse to the convex hull
Print the ellipse shape to make sure it is close to a circle
Draw the convex hull outline in red on the input to check if fits the white region
Draw a circle using the average ellipse radii and center as white filled on black background
Erode the circle a little to avoid leaving a partial white ring
Combine the inverted morph image and the circle image to make a final mask
Apply the final mask to the input
Save the results
import cv2
import numpy as np
# Read image
img = cv2.imread('pills.jpg')
hh, ww = img.shape[:2]
# threshold on white
# Define lower and uppper limits
lower = np.array([200, 200, 200])
upper = np.array([255, 255, 255])
# Create mask to only select black
thresh = cv2.inRange(img, lower, upper)
# apply morphology
kernel = cv2.getStructuringElement(cv2.MORPH_ELLIPSE, (20,20))
morph = cv2.morphologyEx(thresh, cv2.MORPH_CLOSE, kernel)
# get contours
contours = cv2.findContours(morph, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
contours = contours[0] if len(contours) == 2 else contours[1]
# draw white contours on black background as mask
mask = np.zeros((hh,ww), dtype=np.uint8)
for cntr in contours:
cv2.drawContours(mask, [cntr], 0, (255,255,255), -1)
# get convex hull
points = np.column_stack(np.where(thresh.transpose() > 0))
hullpts = cv2.convexHull(points)
((centx,centy), (width,height), angle) = cv2.fitEllipse(hullpts)
print("center x,y:",centx,centy)
print("diameters:",width,height)
print("orientation angle:",angle)
# draw convex hull on image
hull = img.copy()
cv2.polylines(hull, [hullpts], True, (0,0,255), 1)
# create new circle mask from ellipse
circle = np.zeros((hh,ww), dtype=np.uint8)
cx = int(centx)
cy = int(centy)
radius = (width+height)/4
cv2.circle(circle, (cx,cy), int(radius), 255, -1)
# erode circle a bit to avoid a white ring
kernel = cv2.getStructuringElement(cv2.MORPH_ELLIPSE, (6,6))
circle = cv2.morphologyEx(circle, cv2.MORPH_ERODE, kernel)
# combine inverted morph and circle
mask2 = cv2.bitwise_and(255-morph, 255-morph, mask=circle)
# apply mask to image
result = cv2.bitwise_and(img, img, mask=mask2)
# save results
cv2.imwrite('pills_thresh2.jpg', thresh)
cv2.imwrite('pills_morph2.jpg', morph)
cv2.imwrite('pills_mask2.jpg', mask)
cv2.imwrite('pills_hull2.jpg', hull)
cv2.imwrite('pills_circle.jpg', circle)
cv2.imwrite('pills_result2.jpg', result)
cv2.imshow('thresh', thresh)
cv2.imshow('morph', morph)
cv2.imshow('mask', mask)
cv2.imshow('hull', hull)
cv2.imshow('circle', circle)
cv2.imshow('mask2', mask2)
cv2.imshow('result', result)
cv2.waitKey(0)
cv2.destroyAllWindows()
Threshold image:
Morphology image:
Filled contours image:
Convex hull on input:
Circle image:
Final mask image:
Result: