""" ================== Hausdorff Distance ================== This example shows how to calculate the Hausdorff distance between two sets of points. The `Hausdorff distance `__ is the maximum distance between any point on the first set and its nearest point on the second set, and vice-versa. """ import matplotlib.pyplot as plt import numpy as np from skimage import metrics shape = (60, 60) image = np.zeros(shape) # Create a diamond-like shape where the four corners form the 1st set of points x_diamond = 30 y_diamond = 30 r = 10 fig, ax = plt.subplots() plt_x = [0, 1, 0, -1] plt_y = [1, 0, -1, 0] set_ax = [(x_diamond + r * x) for x in plt_x] set_ay = [(y_diamond + r * y) for y in plt_y] plt.plot(set_ax, set_ay, 'or') # Create a kite-like shape where the four corners form the 2nd set of points x_kite = 30 y_kite = 30 x_r = 15 y_r = 20 set_bx = [(x_kite + x_r * x) for x in plt_x] set_by = [(y_kite + y_r * y) for y in plt_y] plt.plot(set_bx, set_by, 'og') # Set up the data to compute the hausdorff distance coords_a = np.zeros(shape, dtype=bool) coords_b = np.zeros(shape, dtype=bool) for x, y in zip(set_ax, set_ay): coords_a[(x, y)] = True for x, y in zip(set_bx, set_by): coords_b[(x, y)] = True # Call the hausdorff function on the coordinates metrics.hausdorff_distance(coords_a, coords_b) # Plot the lines that shows the length of the hausdorff distance x_line = [30, 30] y_line = [20, 10] plt.plot(x_line, y_line, 'y') x_line = [30, 30] y_line = [40, 50] plt.plot(x_line, y_line, 'y') # Plot circles to show that at this distance, the hausdorff distance can # travel to its nearest neighbor (in this case, from the kite to diamond) ax.add_artist(plt.Circle((30, 10), 10, color='y', fill=None)) ax.add_artist(plt.Circle((30, 50), 10, color='y', fill=None)) ax.add_artist(plt.Circle((15, 30), 10, color='y', fill=None)) ax.add_artist(plt.Circle((45, 30), 10, color='y', fill=None)) ax.imshow(image, cmap=plt.cm.gray) ax.axis((0, 60, 60, 0)) plt.show()