How to connect broken lines that cannot be connected by erosion and dilation?

Question

I have an image like this that has multiple stoppers and some of the lines are broken. To connect this broken line, I used a morphological operation like this:

import cv2
import numpy as np

img = cv2.imread('sample.png', cv2.IMREAD_GRAYSCALE)
morph = cv2.morphologyEx(im, cv2.MORPH_CLOSE, np.ones((10,10),np.uint8))

But this didn't connect my broken lines. How can I connect the lines without affecting the other lines?

img

A line break is a break between two small lines in the center of the image. Only the discontinuous part does not have rounded ends.

applied morphological operation

Answer 1

• 1. You can use createFastLineDetector for detecting each line.

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• 2. Calculate the slope of the current and neighboring lines.

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• 3. If the slope of current and neighboring lines are the same draw line.

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Initializing Line Detector

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We will be using ximgproc library for detecting lines.

import cv2

img = cv2.imread("lines.png")
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
d = cv2.ximgproc.createFastLineDetector()
lines = d.detect(gray)

• The lines variable returns similar values like [[14.82, 78.90, 90.89, 120.78]] where x1=14.82, y1=78.90, x2=90.89, y2=120.78 respectively.

Calculating Slope

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• The slope of a line is calculated with the formula: m = (y2 - y1) / (x2 - x1)

• For a given line object, get the coordinates and return the slope.

• def calculate_slope(line_object):
      x_point1 = line_object[0]
      y_point1 = line_object[1]
      x_point2 = line_object[2]
      y_point2 = line_object[3]
  
      m = abs((y_point2 - y_point1) / (x_point2 - x_point1))
      m = float("{:.2f}".format(m))
      return m
  

Comparing Slopes

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• 1. Check the equality of the lines. if the points are equal, that means they are the same line.

  • for current_line in lines:
         current_slope = calculate_slope(current_line[0])
    
         for neighbor_line in lines:
             current_x1 = int(current_line[0][0])
             current_y1 = int(current_line[0][1])
             current_x2 = int(current_line[0][2])
             current_y2 = int(current_line[0][3])
    
             compare_lines = current_line == neighbor_line[0]
             equal_arrays = compare_lines.all()
    

• 2. If the lines are not equal, calculate the neighbor's line slope.

     if not equal_arrays:
         neighbor_slope = calculate_slope(neighbor_line[0])
     

• 3. If slopes are equal, draw the line. From neighbor to current and current to neighbor.

     if abs(current_slope - neighbor_slope) < 1e-3:
         neighbor_x1 = int(neighbor_line[0][0])
         neighbor_y1 = int(neighbor_line[0][1])
         neighbor_x2 = int(neighbor_line[0][2])
         neighbor_y2 = int(neighbor_line[0][3])
     
         cv2.line(img,
                  pt1=(neighbor_x1, neighbor_y1),
                  pt2=(current_x2, current_y2),
                  color=(255, 255, 255),
                  thickness=3)
         cv2.line(img,
                  pt1=(current_x1, current_y1),
                  pt2=(neighbor_x2, neighbor_y2),
                  color=(255, 255, 255),
                  thickness=3)
     

Result

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Possible Question But why couldn't you connect the following parts?

Answer

Well, the red dotted line slopes are not equal. Therefore I couldn't connect them.

Possible Question Why didn't you use dilate and erode methods? as shown in here

Answer

I tried, but the result is not satisfactory.