"""
===================
Label image regions
===================

This example shows how to segment an image with image labelling. The following
steps are applied:

1. Thresholding with automatic Otsu method
2. Close small holes with binary closing
3. Remove artifacts touching image border
4. Measure image regions to filter small objects

"""

import numpy as np
import matplotlib.pyplot as plt
import matplotlib.patches as mpatches

from skimage import data
from skimage.filter import threshold_otsu
from skimage.segmentation import clear_border
from skimage.morphology import label, closing, square
from skimage.measure import regionprops


image = data.coins()[50:-50, 50:-50]

# apply threshold
thresh = threshold_otsu(image)
bw = closing(image > thresh, square(3))

# remove artifacts connected to image border
cleared = bw.copy()
clear_border(cleared)

# label image regions
label_image = label(cleared)
borders = np.logical_xor(bw, cleared)
label_image[borders] = -1

fig, ax = plt.subplots(ncols=1, nrows=1, figsize=(6, 6))
ax.imshow(label_image, cmap='jet')

for region in regionprops(label_image, ['Area', 'BoundingBox']):

    # skip small images
    if region['Area'] < 100:
        continue

    # draw rectangle around segmented coins
    minr, minc, maxr, maxc = region['BoundingBox']
    rect = mpatches.Rectangle((minc, minr), maxc - minc, maxr - minr,
                              fill=False, edgecolor='red', linewidth=2)
    ax.add_patch(rect)

plt.show()