PIL/Numpy: enlarging white areas of black/white mask image-CodePudding

I want to produce a Python algorithm which takes in a 'mask' RGB image comprised exclusively of black and white pixels. Basically, each mask is a black image with one or more white shapes on it (see below).

I want to transform this image by enlarging the white areas by a factor x:

So far I have only got it to work by drawing rectangles around the shapes using PIL:

def add_padding_to_mask(mask, padding):
    # Create a copy of the original mask
    padded_mask = mask.copy()
    draw = ImageDraw.Draw(padded_mask)

    # Iterate over the pixels in the original mask
    for x in range(mask.width):
        for y in range(mask.height):
            # If the pixel is white, draw a white rectangle with the desired padding around it
            if mask.getpixel((x, y)) == (255, 255, 255):
                draw.rectangle((x-padding, y-padding, x padding, y padding), fill=(255, 255, 255))

    return padded_mask

This is suboptimal since I want to retain the original white shapes (only make them larger). I can't figure out an efficient way to approach this problem. Any help greatly appreciated.

CodePudding user response：

If you want to enlarge a white object on a black background, you can use "morphological dilation". There are many tools/methods:

The simplest is with ImageMagick on the command-line, e.g.:

magick XlAiE.png -morphology dilate disk:3.5 result.png

There are lots of examples

Reduce the (9,9) to, say (3,3) for less dilation, or increase it to, say (20,20) for more dilation.

If you just want to dilate vertically, use a tall thin structuring element:

SE = np.ones((20,1), np.uint8)
res = cv2.morphologyEx(im, cv2.MORPH_DILATE, SE)

If you just want to dilate horizontally, use a wide thin structuring element:

SE = np.ones((1,20), np.uint8)
res = cv2.morphologyEx(im, cv2.MORPH_DILATE, SE)