# How to separate text from the paper on a black and white page?

I tried to discretize an image into black and white and came into some difficult. The difference between the letters and paper is pretty clear to our eyes:

However a simple thresholding trick doesn't work. Here we move everything below 0.4 intensity to 0 and everything above 0.4 to 1:

Now let's try moving the threshhold to 0.5 and some nasty artifacts occur:

I wish I could take the "best of both worlds" of trial 1 or trial 2. Here is the Python code I used... basically the introductory tutorial with a few changes:

from skimage import io
from skimage import color
import numpy as np

import matplotlib.pyplot as plt
%matplotlib inline
plt.rcParams['figure.figsize'] = 7,7

io.imshow(poem)
io.show()

poem_gray = color.rgb2gray(poem)

t = 0.5
poem_gray[poem_gray < t] = 0
poem_gray[poem_gray > t] = 1
io.imshow(poem_gray)
io.show()


Here is the histogram for black and white in my image, to justify my threshhold of about 0.45 My eyes are playing tricks on me!! Some of the "white section" is as dark as the text. Is there a more standard method for separating grayscale images?

• You could split the image into rectangular areas and apply different thresholds to each area. – Biswajit Banerjee Nov 21 '15 at 1:20

I believe the best approach here is to use a threshold based on the local average brightness of the image. Setting the threshold to be 90% of the mean value of the 11x11 grid surrounding each pixel gives results that are about as good as you can expect with such a low resolution image.

For each pixel you just need to compute the mean brightness of the pixels near it. Then, if the pixel's brightness is less than 0.9 (or some threshold of your choosing) times the mean set it to black, otherwise set it to white.