4 corners of a playingcard with contours

Question

Im trying to find coordinates of 4 corners of a playingcard so i can use it to warpPerspective of the card and later use for recognition. I have tried using cv.boundingRect, but as im using a live videofeed, i only need the card and not the closest rectangle of the card. Right now it works using boundingRect, but if i tilt the angle of the image the coordinates are of the boundingRect and not the playing card. See pictures:
straight angle …
crooked angle

I then need the coordinates of my contour for the 4 corners of the playing card, not using boundingRect.
This is my method so far:

def getContours(img, imgContour, standardimg):
global counter
contours, hierachy = cv2.findContours(img, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_NONE)

for contour in contours:
    area = cv2.contourArea(contour)
    areaMin = cv2.getTrackbarPos("area", "parameters")
    if area > areaMin:
        cv2.drawContours(imgContour, contour, -1, (255, 0, 255), 5)
        peri = cv2.arcLength(contour, True)
        approx = cv2.approxPolyDP(contour, 0.04 * peri, True)

        if len(approx) == 4:
            x, y, w, h = cv2.boundingRect(approx)

            cv2.rectangle(imgContour, (x, y), (x + w, y + h), (255, 255, 0), 3)


            cv2.putText(imgContour, "Area: " + str(int(area)), (x + w + 20, y + 45), cv2.FONT_HERSHEY_COMPLEX, 0.7,
                        (0, 255, 0), 2)

            if cv2.waitKey(1) & 0xFF == ord('c'):
                counter = counter + 1
                cv2.imwrite('warpedPicture' + str(counter) + '.jpg', imgContour)

                coordinates.insert(0, x)
                coordinates.insert(1, y)
                coordinates.insert(2, h)
                coordinates.insert(3, w)
                warpPicture(coordinates[0], coordinates[1], coordinates[2], coordinates[3], standardimg)

Asked By: Itstudentwithnoknowledge

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Source

Answer 1

One possible method in Python/OpenCV that is likely better than just the bounding box is as follows:

Read the input
Convert to gray
Threshold
Get the external contour
Compute the perimeter
Approximate the contour as a quadrilateral
Draw the quadrilateral on the input
Save the result

Input A:

import cv2
import numpy as np

# load image
img = cv2.imread("5_hearts_A.png")
hh, ww = img.shape[:2]

# convert to gray
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)

# threshold the grayscale image
thresh = cv2.threshold(gray, 0, 255, cv2.THRESH_BINARY+cv2.THRESH_OTSU)[1]

# remove white borders
thresh = thresh[2:hh-2, 2:ww-2]
thresh = cv2.copyMakeBorder(thresh, 2,2,2,2, cv2.BORDER_REPLICATE)

# find outer contour
cntrs = cv2.findContours(thresh, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
cntrs = cntrs[0] if len(cntrs) == 2 else cntrs[1]
cntr = cntrs[0]

# draw contour on copy of img as result
contour = img.copy()
cv2.drawContours(contour,[cntr], 0, (0,0,255), 1)

# limit contour to quadrilateral
peri = cv2.arcLength(cntr, True)
corners = cv2.approxPolyDP(cntr, 0.04 * peri, True)

# draw quadrilateral on input image from detected corners
result = img.copy()
cv2.polylines(result, [corners], True, (0,0,255), 1, cv2.LINE_AA)

# write result to disk
cv2.imwrite("5_hearts_A_contour.png", contour)
cv2.imwrite("5_hearts_A_quadrilateral.png", result)

# display results
cv2.imshow("THRESH", thresh)
cv2.imshow("CONTOUR", contour)
cv2.imshow("QUAD", result)
cv2.waitKey(0)
cv2.destroyAllWindows()

Contour image:

Resulting quadrilateral:

Similarly for Image B:

Contour for Image B:

Result for Image B:

An approach that likely would do better would be to do Canny edge detection on the thresholded image. Then Hough line transform. And then compute the intersections of the lines to find to corners.

Answered By: fmw42

4 corners of a playingcard with contours

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