I would like to approximate smooth lines with chain of line segments.
cv2.approxPolyDP in OpenCV 3.4 made a good result in the case of closed curve.
Origin close curve:
Approximated close curve:
But in the case of open curve, cv2.approxPolyDP did not achieve the desired effect.
Origin open curve:
Approximated open curve:
The result I want should be one chain of line segments but not a closed polygon, like this(this picture is created by Photoshop but not Python program):
Is there a way to use cv2.approxPolyDP to approximate open curve?
My Python program is as follow:
import cv2
img = cv2.imread('1.jpg')
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
cv2.imshow("gray", gray)
cv2.waitKey(0)
_, binary = cv2.threshold(gray, 10, 255, cv2.THRESH_BINARY)
# cv2.imshow("binary", binary)
# cv2.waitKey(0)
_, contours, _ = cv2.findContours(binary, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
for contour in contours:
epsilon = 0.009 * cv2.arcLength(contour, True)
approx = cv2.approxPolyDP(contour, epsilon, closed=True)
cv2.drawContours(img, [approx], -1, (0, 255, 255), 1)
cv2.imshow("approx", img)
cv2.waitKey(0)
cv2.destroyAllWindows()
The origin photos used in my program are as follow.
Close curve photo Open curve photo
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Answer
Here is how to do that in Python/OpenCV using cv2.approxPolyDP
Input (cropped off screen snap title bar)
import numpy as np
import cv2
# read input
img = cv2.imread('curve.png')
hh, ww = img.shape[:2]
# convert to grayscale
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
# threshold
thresh = cv2.threshold(gray, 100, 255, cv2.THRESH_BINARY)[1]
# get points
points = np.column_stack(np.where(thresh.transpose() != 0))
# list points
for pt in points:
ptx = pt[0]
pty = pt[1]
print(ptx,pty)
# approximate polygon
poly = cv2.approxPolyDP(points, 0.02 * ww, False)
# list polygon points
for p in poly:
px = p[0]
py = p[0]
print(px,py)
# draw polygon on copy of input
result = img.copy()
cv2.polylines(result, [poly], False, (0,0,255), 1)
# save results
cv2.imwrite('curve_polygon.png', result)
cv2.imshow("thresh", thresh)
cv2.imshow("result", result)
cv2.waitKey(0)