Compare Current Pixel Value With The Previous One On Numpy Array

Is possible to implement this image filtering process in numpy array ? I need to check if the pixel in the previous column and previous row is differente of the current pixel. widt

Solution 1:

Here's one approach. Take an example image:

You didn't say where your orig_bin came from, so I've used scipy.misc.imread:

from scipy.misc import imread, imsaveimg= imread('input.png')

First, create a mask for pixels that are different from the pixel above (this uses an idea from Bi Rico's answer):

up   = (img[1:,1:] != img[:-1,1:]).any(axis=2)

Note that imread loads images in row-major order, so the first NumPy axis is the vertical axis. See "Multidimensional Array Indexing Order Issues" for an explanation.

Similarly, create a mask for pixels that are different from the pixel to the left:

left = (img[1:,1:] != img[1:,:-1]).any(axis=2)

Combine these to get a mask for pixels that are different to either the pixel above or left:

mask = numpy.zeros(img.shape[:2], dtype=bool)
mask[1:,1:] = left | up

Create a black output image of the right size; then set the mask to white:

output = numpy.zeros(img.shape)
output[mask] = (255, 255, 255)
imsave('output.png', output)

And here's the result:

or if you want the colours to be the other way round, invert the mask:

output[~mask] = (255, 255, 255)

Solution 2:

You want something like:

change = (pixels[1:, 1:] != pixels[1:, :-1]) | (pixels[1:, 1:] != pixels[:-1, 1:])

This will be binary (True, False), you'll need to multiply it by 255 if you want your result to be 0/255. You also might need to run and any on the last dimension if you array is (x, y, 3).

There are other ways you could re-cast this problem, for example a convolution with [1, -1] might get you most of the way there.