python-3.x - 计算特定暗区的平均宽度

Question

我正在处理与以下图像相似的大部分图像。我希望能够计算黑线(图像中大致为黄线)的平均宽度，但是不确定如何在python中最好地做到这一点。黄线本身不出现在图像上，仅出现黑带。

原始图像:

Answer 1

第一种方法是使用line-detector。

查找图像的边缘

img = cv2.imread('calculate_width.png')
gray_img = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
canny_img = cv2.Canny(gray_img, threshold1=150, threshold2=200)

检测行

lines = createFastLineDetector(_length_threshold=20).detect(canny_img)

计算距离

for cur in lines:
    (x1, y1, x2, y2) = cur[0]
    dist = math.sqrt(((x2 - x1) ** 2) + ((y2 - y1) ** 2))
    print("Distance between ({:.2f}, {:.2f}) - ({:.2f}, {:.2f}) = {:.2f}"
          .format(x1, y1, x2, y2, dist))
    cv2.line(img, pt1=(x1, y1), pt2=(x2, y2), color=(0, 255, 0),
             thickness=2)
    cv2.imshow("detected", img)
    cv2.waitKey(0)

结果

Distance between (46.98, 884.00) - (50.37, 905.10) = 21.37 pixel

更新

如果我们将 image-segmentation应用于以下区域:

我们想使用公式找到红线的长度并找到红线之间的距离。

上层:

Distance between (118.06, 868.42) - (96.92, 871.40)
Distance between (95.94, 872.67) - (75.85, 876.11) 
Distance between (74.88, 877.33) - (24.85, 886.16) 
Distance between (23.96, 887.62) - (0.01, 890.06) 

下层:

Distance between (79.07, 894.60) - (99.02, 892.15)
Distance between (104.01, 886.54) - (125.99, 887.20)
Distance between (40.93, 901.45) - (66.05, 898.40)
Distance between (0.00, 906.02) - (33.99, 905.52) 

如果您随机选择两个点: (66.05, 898.40)和 (24.85 - 886.16)，则距离为: 41.23解决方案不是完美的，但是它可能会给人一个更好的主意的直觉。因此，我将其发布为答案。
码:

import cv2
import math
import numpy as np
from cv2.ximgproc import createFastLineDetector

img = cv2.imread('calculate_width.png')
gray_img = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
ret, thresh = cv2.threshold(gray_img, 150, 255,
                            cv2.THRESH_BINARY_INV + cv2.THRESH_OTSU)
kernel = np.ones((5, 5), np.uint8)
opening = cv2.morphologyEx(thresh, cv2.MORPH_OPEN, kernel)
sure_bg = cv2.dilate(opening, kernel)
dist_transform = cv2.distanceTransform(opening, cv2.DIST_L2, 5)
_, sure_fg = cv2.threshold(dist_transform, 0.3*dist_transform.max(),
                           255, 0)
sure_fg = np.uint8(sure_fg)
unknown = cv2.subtract(sure_bg, sure_fg)

lines = createFastLineDetector(_length_threshold=20).detect(unknown)

for cur in lines:
    (x1, y1, x2, y2) = cur[0]
    dist = math.sqrt(((x2 - x1) ** 2) + ((y2 - y1) ** 2))
    print("Distance between ({:.2f}, {:.2f}) - ({:.2f}, {:.2f})"
          .format(x1, y1, x2, y2))
    cv2.line(img, pt1=(x1, y1), pt2=(x2, y2), color=(0, 255, 0),
             thickness=2)
    cv2.imshow("detected", img)
    cv2.waitKey(0)