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pythonnumpyopencvopencv3.0edge-detection

How to extract a specific section of an image using OpenCV in Python?

I am trying to extract a portion of an image by performing Canny edge detection. I have succesfully created a mask of that object. But when I perform a bitwise_and operation with the original image, to extract the foreground section, I am getting the following error .

OpenCV Error: Assertion failed ((mtype == CV_8U || mtype == CV_8S) && _mask.sameSize(*psrc1)) in cv::binary_op, file C:\projects\opencv-python\opencv\modules\core\src\arithm.cpp, line 241
    Traceback (most recent call last):
      File "C:\Users\Boudhayan Dev\Desktop\extraction.py", line 37, in <module>
        new_image = cv2.bitwise_and(img_rgb,img_rgb,mask=mask)
    cv2.error: C:\projects\opencv-python\opencv\modules\core\src\arithm.cpp:241: error: (-215) (mtype == CV_8U || mtype == CV_8S) && _mask.sameSize(*psrc1) in function cv::binary_op

My code is as follows -

import cv2
import numpy as np

img_rgb = cv2.imread("3.jpg")
cv2.namedWindow("Original Image",cv2.WINDOW_NORMAL)

img = cv2.cvtColor(img_rgb,cv2.COLOR_RGB2HSV)
img = cv2.bilateralFilter(img,9,105,105)
r,g,b=cv2.split(img)
equalize1= cv2.equalizeHist(r)
equalize2= cv2.equalizeHist(g)
equalize3= cv2.equalizeHist(b)
equalize=cv2.merge((r,g,b))

equalize = cv2.cvtColor(equalize,cv2.COLOR_RGB2GRAY)

ret,thresh_image = cv2.threshold(equalize,0,255,cv2.THRESH_OTSU+cv2.THRESH_BINARY)
equalize= cv2.equalizeHist(thresh_image)


canny_image = cv2.Canny(equalize,250,255)
canny_image = cv2.convertScaleAbs(canny_image)
kernel = np.ones((3,3), np.uint8)
dilated_image = cv2.dilate(canny_image,kernel,iterations=1)


new,contours, hierarchy = cv2.findContours(dilated_image, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
contours= sorted(contours, key = cv2.contourArea, reverse = True)[:10]
c=contours[0]
print(cv2.contourArea(c))
final = cv2.drawContours(img, [c], -1, (255,0, 0), 3)



mask = np.zeros(img_rgb.shape,np.uint8)
new_image = cv2.drawContours(mask,[c],0,255,-1,)
new_image = cv2.bitwise_and(img_rgb,img_rgb,mask=mask)


cv2.namedWindow("new",cv2.WINDOW_NORMAL)
cv2.imshow("new",new_image)

cv2.imshow("Original Image",img)
cv2.waitKey()

NOTE :- The code works fine if I try to perform the bitwise_and with a grayscale version of the image. However RGB,HSV or any other color spaces give the error above.

Please help.

EDIT 1 - The image in question is this -

3.jpeg

EDIT 2-

The following is the result after using Numpy method. As you can see, the extracted image is the same size as the orange but it does not contain the orange instead the mask itself.

result

EDIT 3- @DanMašek and @lightalchemist , I could finally extract any foreground image.

result1

result2

Thank you

Solution

  • I used the code provided above but only altered the line where the cv2.bitwise_and() is used:

    new_image = cv2.bitwise_and(img_rgb, img_rgb, mask = equalize)

    This is what I got and what you expected (I guess):

    enter image description here

    EDIT

    I get it, you want to mask your image with an image of contour having the greatest area. In the following additional snippet I have binarized the image containing the contour of greatest area to be used as mask.

    new_image = cv2.drawContours(mask,[c], -1, (255,255,255), -1)
new_image_gray = cv2.cvtColor(new_image, cv2.COLOR_BGR2GRAY)
ret, thresh1 = cv2.threshold(new_image_gray, 100, 255, cv2.THRESH_BINARY)
final = cv2.bitwise_and(img_rgb, img_rgb, mask = thresh1)

    This is what I got:

    enter image description here

    Compared to the image above you do not see those holes inside the object of interest.