Detect objects that are located on the side of an image opencv

Question

I am trying to detect several objects in an image; however, some objects are located at the edge, so not all contours are shown in the image. How can we detect objects that are "cropped" in a way? Can we enclose the contours at the edges of an image?

First, I blurred the image, applied a canny detector, dilated, and then eroded the edges.
Here is my code:

img = cv2.imread('porosity1.png')

img1 = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)

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

blur = cv2.GaussianBlur(gray, (7,7),0)

med = np.median(blur)

lower = int(max(0,0.7*med))

upper = int(min(255,1.3*med))

edged = cv2.Canny(blur, lower, upper)

edged = cv2.dilate(edged, None, iterations=1)
edged = cv2.erode(edged, None, iterations=1)

This is what I get for edge detection, which is fine with me.

enter image description here

But when I want to fill my contours to check if the detector was able to detect all objects (even the ones at the side of the image) I get this:

gray, cnts, hierarchy = cv2.findContours(edged, mode = cv2.RETR_CCOMP,method = cv2.CHAIN_APPROX_NONE )

cnts1 = []

external_contours = np.zeros(gray.shape)

for i,cnt in enumerate(cnts):
    
    
    #External contours
    if cv2.contourArea(cnt)>100.0: #To exclude small contour areas
        cv2.drawContours(external_contours, cnts, i, 1, -1)
        cnts1.append(cnt)
        
        
        #Last column in each row in the hierarchy

plt.imshow(external_contours, cmap='gray')

enter image description here

The reason I want to detect is that I want to find the enclosed area of the objects.

Answer 1

You can use cv2.convexHull function on the found contours, then the contours on the edges will be closed.