How to fill holes or reduce noise in an image?

Issue

I need to reduce the noise in images like the one bellow, i.e. fill the holes in the white object. I tried something with opencv but it ended up removing part of the object as you can see. Is there a better way to do this without losing the object itself? Any help is appreciated!

Here’s what I have so far:

import numpy as np
import cv2

def remove_noise(gray, num):
    Y, X = gray.shape
    nearest_neigbours = [[
        np.argmax(
            np.bincount(
                gray[max(i - num, 0):min(i + num, Y), max(j - num, 0):min(j + num, X)].ravel()))
        for j in range(X)] for i in range(Y)]
    result = np.array(nearest_neigbours, dtype=np.uint8)
    cv2.imwrite('result.png', result)
    return result

img = cv2.imread('img.png')
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)

remove_noise(gray, 10)

Input image:

enter image description here

Output image:

enter image description here

Solution

Following @JeruLuke‘s suggestion, I used cv.morphologyEx(img, cv.MORPH_CLOSE, kernel) and got the result I wanted with the following code snippet.

import cv2
import numpy as np

image = cv2.imread('image.png')
gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
kernel_size = (7, 7)

kernel = cv2.getStructuringElement(cv2.MORPH_RECT, kernel_size)
closing = cv2.morphologyEx(gray, cv2.MORPH_CLOSE, kernel)
cv2.imwrite('result.png', closing)

Output image:

enter image description here

Answered By – Davi Magalhães

Answer Checked By – Marie Seifert (AngularFixing Admin)

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