import cv2
import numpy as np
import matplotlib.pyplot as plt

def show(img):
    plt.figure(figsize=(10,10))
    plt.imshow(img,cmap='gray')
    plt.show()


image = cv2.imread('receipt-1.jpg', cv2.IMREAD_GRAYSCALE)

cv2.fastNlMeansDenoising(image, image, 10, 5, 11)

thresh = cv2.adaptiveThreshold(image, 255, 1, 1, 11, 2)

kernel = np.ones((1,5), np.uint8)
img_dilation = cv2.dilate(thresh, kernel, iterations=1)

# find contours
_,ctrs,_ = cv2.findContours(img_dilation,cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)

# Sort contours
sorted_ctrs = sorted(ctrs,key=cv2.contourArea)


result = cv2.cvtColor(image, cv2.COLOR_GRAY2BGR)

for i, ctr in enumerate(sorted_ctrs):
    x, y, w, h = cv2.boundingRect(ctr)
    if h > 50: continue
    roi = thresh[y:y+h, x:x+w]
    result[y:y+h, x:x+w, 0] = 0
    result[y:y+h, x:x+w, 1] = 255

show(result)