The following code block shows how the remove_small_objects() function can be used to remove objects smaller than a specified minimum size threshold—the higher the specified threshold, the more objects get removed:
from skimage.morphology import remove_small_objectsim = rgb2gray(imread('../images/circles.jpg'))im[im > 0.5] = 1 # create binary image by thresholding with fixed threshold0.5im[im <= 0.5] = 0im = im.astype(np.bool)pylab.figure(figsize=(20,20))pylab.subplot(2,2,1), plot_image(im, 'original')i = 2for osz in [50, 200, 500]: im1 = remove_small_objects(im, osz, connectivity=1) pylab.subplot(2,2,i), plot_image(im1, 'removing small objects below size ' + str(osz)) i += 1pylab.show()
The following screenshot shows ...
