如何找到不同角度的两个同心轮廓之间的距离? [英] How to find the distance between two concentric contours, for different angles?

问题描述

我有一个具有两个轮廓的图像，其中一个轮廓总是在另一个轮廓内部".我想找到90个不同角度的两个轮廓之间的距离(即每4度的距离).我该怎么做?

I have an image with two contours, where one contour is always 'inside' another. I want to find the distance between the two contours for 90 different angles (meaning, distance at every 4 degrees). How do I go about doing it?

这是一个示例图片:

谢谢！

推荐答案

在下面的代码中，我刚刚为您提供了垂直线的示例，其余的可以通过旋转线来获得.结果看起来像这样，您可以使用坐标进行距离计算，而不必绘制图形.

In the following code, I have just given you the example for the vertical line, the rest can be obtained by rotating the line. Result looks like this, instead of drawing you can use the coordinates for distance calculation.

import shapely.geometry as shapgeo
import numpy as np
import cv2


img = cv2.imread('image.jpg', 0)
ret, img =cv2.threshold(img, 128, 255, cv2.THRESH_BINARY)

#Fit the ellipses
_, contours0, hierarchy = cv2.findContours( img.copy(), cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
outer_ellipse = [cv2.approxPolyDP(contours0[0], 0.1, True)]
inner_ellipse = [cv2.approxPolyDP(contours0[2], 0.1, True)]

h, w = img.shape[:2]
vis = np.zeros((h, w, 3), np.uint8)
cv2.drawContours( vis, outer_ellipse, -1, (255,0,0), 1)
cv2.drawContours( vis, inner_ellipse, -1, (0,0,255), 1)

##Extract contour of ellipses
cnt_outer = np.vstack(outer_ellipse).squeeze()
cnt_inner = np.vstack(inner_ellipse).squeeze()

#Determine centroid
M = cv2.moments(cnt_inner)
cx = int(M['m10']/M['m00'])
cy = int(M['m01']/M['m00'])
print cx, cy

#Draw full segment lines 
cv2.line(vis,(cx,0),(cx,w),(150,0,0),1)

# Calculate intersections using Shapely
# http://toblerity.org/shapely/manual.html
PolygonEllipse_outer= shapgeo.asLineString(cnt_outer)
PolygonEllipse_inner= shapgeo.asLineString(cnt_inner)
PolygonVerticalLine=shapgeo.LineString([(cx,0),(cx,w)])


insecouter= np.array(PolygonEllipse_outer.intersection(PolygonVerticalLine)).astype(np.int)
insecinner= np.array(PolygonEllipse_inner.intersection(PolygonVerticalLine)).astype(np.int)
cv2.line(vis,(insecouter[0,0], insecinner[1,1]),(insecouter[1,0], insecouter[1,1]),(0,255,0),2)
cv2.line(vis,(insecouter[0,0], insecinner[0,1]),(insecouter[1,0], insecouter[0,1]),(0,255,0),2)

cv2.imshow('contours', vis)

0xFF & cv2.waitKey()
cv2.destroyAllWindows()  

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