I am trying to remove 5 lines from my image. I tried using the Hough's Transform but none of the results focuses on the lines its always cleaning something on the image. I am quite a novice at image processing. So you could point me to the right direction.
this is my code
import cv2
import numpy as np
# Read in image, grayscale, and Otsu's threshold
image = cv2.imread('C:/Users/User/Downloads/WhatsApp Image 2023-07-17 at 7.17.09 PM.jpeg')
gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
thresh = cv2.threshold(gray, 0, 255, cv2.THRESH_BINARY_INV + cv2.THRESH_OTSU)[1]
# Create diagonal kernel
kernel = np.array([[0, 0, 1],
[0, 1, 0],
[1, 0, 0]], dtype=np.uint8)
opening = cv2.morphologyEx(thresh, cv2.MORPH_OPEN, kernel, iterations=1)
# Find contours and filter using contour area to remove noise
cnts = cv2.findContours(opening, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
cnts = cnts[0] if len(cnts) == 2 else cnts[1]
for c in cnts:
area = cv2.contourArea(c)
if area < 500:
cv2.drawContours(opening, [c], -1, (0, 0, 0), -1)
# Apply Hough Transform to detect lines
lines = cv2.HoughLines(opening, 1, np.pi / 180, threshold=1000)
# Convert lines to white pixels in the image
if lines is not None:
for rho, theta in lines[:, 0]:
a = np.cos(theta)
b = np.sin(theta)
x0 = a * rho
y0 = b * rho
x1 = int(x0 + 1000 * (-b))
y1 = int(y0 + 1000 * (a))
x2 = int(x0 - 1000 * (-b))
y2 = int(y0 - 1000 * (a))
cv2.line(image, (x1, y1), (x2, y2), (255, 255, 255), 2)
# Apply median filter to the image
median_filtered = cv2.medianBlur(image, 5)
# Display the images
cv2.imshow('Original Image', image)
cv2.imshow('Median Filtered Image', median_filtered)
cv2.waitKey(0)
cv2.destroyAllWindows()
Resulting image:
