Removing Horizontal Lines in image (OpenCV, Python, Matplotlib)

Question

Using the following code I can remove horizontal lines in images. See result below.

import cv2
from matplotlib import pyplot as plt

img = cv2.imread(\'image         


        

Answer 1

Here's an approach

• Convert image to grayscale
• Otsu's threshold
• Create special horizontal kernel to detect horizontal lines
• Find contours on mask
• Repair image

---

After converting to grayscale, we Otsu's threshold to obtain a binary image

image = cv2.imread('1.png')
gray = cv2.cvtColor(image,cv2.COLOR_BGR2GRAY)
thresh = cv2.threshold(gray, 0, 255, cv2.THRESH_BINARY_INV + cv2.THRESH_OTSU)[1]

Next we create a special horizontal kernel to detect horizontal lines. We draw these lines onto a mask and then find contours on the mask. To remove the lines, we fill in the contours with white

Detected lines

Mask

Filled in contours

# Remove horizontal
horizontal_kernel = cv2.getStructuringElement(cv2.MORPH_RECT, (25,1))
detected_lines = cv2.morphologyEx(thresh, cv2.MORPH_OPEN, horizontal_kernel, iterations=2)
cnts = cv2.findContours(detected_lines, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
cnts = cnts[0] if len(cnts) == 2 else cnts[1]
for c in cnts:
    cv2.drawContours(image, [c], -1, (255,255,255), 2)

The image currently has gaps. To fix this, we construct a vertical kernel to repair the image

# Repair image
repair_kernel = cv2.getStructuringElement(cv2.MORPH_RECT, (1,6))
result = 255 - cv2.morphologyEx(255 - image, cv2.MORPH_CLOSE, repair_kernel, iterations=1)

Note depending on the image, the size of the kernel will change. For instance, to detect longer lines, we could use a (50,1) kernel instead. If we wanted thicker lines, we could increase the 2nd parameter to say (50,2).

Here's the results with the other images

Detected lines

Original (left), removed (right)

---

Detected lines

Original (left), removed (right)

Full code

import cv2

image = cv2.imread('1.png')
gray = cv2.cvtColor(image,cv2.COLOR_BGR2GRAY)
thresh = cv2.threshold(gray, 0, 255, cv2.THRESH_BINARY_INV + cv2.THRESH_OTSU)[1]

# Remove horizontal
horizontal_kernel = cv2.getStructuringElement(cv2.MORPH_RECT, (25,1))
detected_lines = cv2.morphologyEx(thresh, cv2.MORPH_OPEN, horizontal_kernel, iterations=2)
cnts = cv2.findContours(detected_lines, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
cnts = cnts[0] if len(cnts) == 2 else cnts[1]
for c in cnts:
    cv2.drawContours(image, [c], -1, (255,255,255), 2)

# Repair image
repair_kernel = cv2.getStructuringElement(cv2.MORPH_RECT, (1,6))
result = 255 - cv2.morphologyEx(255 - image, cv2.MORPH_CLOSE, repair_kernel, iterations=1)

cv2.imshow('thresh', thresh)
cv2.imshow('detected_lines', detected_lines)
cv2.imshow('image', image)
cv2.imshow('result', result)
cv2.waitKey()