Improving the image for 4-point contour approximation

Python
1

Hi everyone,

I’m creating a YuGiOh card detector based exclusively on OpenCV and Tesseract OCR.
First I make a binary image and then find the contours that can be approximated with 4 points. The problem is that sometimes the edges of the borders are smoothed out as seen in the example below:

dilated
dilated799×796 6.94 KB

As you can see the edges on the card in the middle are quite smooth even though they are not in the original image which is why the 4-point approximation fails I presume.

This is the code for getting the binary image.

    #grayscale -> bluring -> canny thresholding -> dilation
    gray_img = cv2.cvtColor(img_resized, cv2.COLOR_BGR2GRAY)
    blur = cv2.GaussianBlur(gray_img, (11,11), 0)
    thresh = cv2.Canny(blur, 50, 100)
    dilated = cv2.dilate(thresh, np.ones((11,11), dtype=np.int8))

This is the code for 4-point contour approximation.

    tbd = list()
    for c in contours:
        peri = cv2.arcLength(c, True)
        approx = cv2.approxPolyDP(c, 0.05 * peri, True)
        if len(approx) == 4:
            tbd.append(approx)

If someone could point me in the right direction to fix this type of problem I would be very grateful. Thanks in advance! :slight_smile: