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I have a batch of images which I would like to scan. Some of them have got a horizontal line crossing the characters that have to be scanned, which would look like this:

Raw Image

I have made a program that is able to remove the horizontal line:

import cv2
import numpy as np

img = cv2.imread('image.jpg',0)

# Applies threshold and inverts the image colors
(thresh, im_bw) = cv2.threshold(img, 128, 255, cv2.THRESH_BINARY | cv2.THRESH_OTSU)
im_wb = (255-im_bw)

# Line parameters
minLineLength = 100
maxLineGap = 10
color = 255
size = 2

# Substracts the black line
lines = cv2.HoughLinesP(im_wb,1,np.pi/180,minLineLength,maxLineGap)[0]
for x1,y1,x2,y2 in lines:
    cv2.line(img,(x1,y1),(x2,y2),color,size) 

cv2.imshow('clean', img)

This returns the image below:

Clean Image

So, do you have any idea of how to make OCR to these characters that have the white line crossing them? Would you make a different approach than the one stated?

Please ask any questions you have if something is not clear. Thank you.

ebeneditos
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    Have you tried writing an algorithm that removes only the portions of the black line outside the character strokes it crosses? I would recommend focusing on that. Once you know the line thickness (assuming it has a consistent thickness), you could check whether there are black pixels above and below the line, and only remove the line one column at a time if the pixels above and below are white. – Rethunk Dec 15 '16 at 04:48

1 Answers1

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Following @Rethunk advice, I did the following:

# Line parameters
minLineLength = 100
maxLineGap = 10
color = 255
size = 1

# Substracts the black line
lines = cv2.HoughLinesP(im_wb,1,np.pi/180,minLineLength,maxLineGap)[0]

# Makes a list of the y's located at position x0 and x1
y0_list = []
y1_list = []
for x0,y0,x1,y1 in lines:
    if x0 == 0:
        y0_list.append(y0)
    if x1 == im_wb.shape[1]:
        y1_list.append(y1)

# Calculates line thickness and its half
thick = max(len(y0_list), len(y1_list))
hthick = int(thick/2)

# Initial and ending point of the full line
x0, x1, y0, y1 = (0, im_wb.shape[1], sum(y0_list)/len(y0_list), sum(y1_list)/len(y1_list))

# Iterates all x's and prints makes a vertical line with the desired thickness 
# when the point is surrounded by white pixels
for x in range(x1):
    y = int(x*(y1-y0)/x1) + y0
    if im_wb[y+hthick+1, x] == 0 and im_wb[y-hthick-1, x] == 0:
        cv2.line(img,(x,y-hthick),(x,y+hthick),colour,size) 

cv2.imshow(clean', img)

So, as the HoughLinesP function returns the initial and final point of horizontal lines, I made a list of the y coordinates of the points that are in the begginning and end of the image and thus I am able to know the full line equation (so if it is inclined is valid as well) and I can iterate all its points. For each point, if it is surrounded by white pixels, I remove it. The outcome is the following:

enter image description here

If you have any better idea please tell!

ebeneditos
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