Remove noise from threshold image opencv python

Question

I am trying to get the corners of the box in image. Following are example images, their threshold results and on the right after the arrow are the results that I need. You m

Answer 1

Below is a python implementation of @dhanushka's approach

import cv2
import numpy as np

# load color image
im = cv2.imread('input.jpg')

# smooth the image with alternative closing and opening
# with an enlarging kernel
morph = im.copy()

kernel = cv2.getStructuringElement(cv2.MORPH_RECT, (1, 1))
morph = cv2.morphologyEx(morph, cv2.MORPH_CLOSE, kernel)
morph = cv2.morphologyEx(morph, cv2.MORPH_OPEN, kernel)

kernel = cv2.getStructuringElement(cv2.MORPH_RECT, (2, 2))

# take morphological gradient
gradient_image = cv2.morphologyEx(morph, cv2.MORPH_GRADIENT, kernel)

# split the gradient image into channels
image_channels = np.split(np.asarray(gradient_image), 3, axis=2)

channel_height, channel_width, _ = image_channels[0].shape

# apply Otsu threshold to each channel
for i in range(0, 3):
    _, image_channels[i] = cv2.threshold(~image_channels[i], 0, 255, cv2.THRESH_OTSU | cv2.THRESH_BINARY)
    image_channels[i] = np.reshape(image_channels[i], newshape=(channel_height, channel_width, 1))

# merge the channels
image_channels = np.concatenate((image_channels[0], image_channels[1], image_channels[2]), axis=2)

# save the denoised image
cv2.imwrite('output.jpg', image_channels)

The above code doesn't give good results if the image you are dealing are invoices(or has large amount of text on a white background). In order to get good results on such images, remove

gradient_image = cv2.morphologyEx(morph, cv2.MORPH_GRADIENT, kernel)

and pass morph obj to the split function and remove the ~ symbol inside for loop