mirror of
https://github.com/wassname/scikit-image.git
synced 2026-06-27 19:48:43 +08:00
Johannes Schönberger
63 lines
1.8 KiB
Python
63 lines
1.8 KiB
Python
"""
|
|
===============================================
|
|
Local Binary Pattern for texture classification
|
|
===============================================
|
|
|
|
In this example, we will see how to classify textures based on LBP (Local Binary
|
|
Pattern). The histogram of the LBP result is a good measure to classify
|
|
textures. For simplicity the histogram distributions are then tested against
|
|
each other using the Kullback-Leibler-Divergence.
|
|
"""
|
|
|
|
import os
|
|
import glob
|
|
import numpy as np
|
|
import pylab
|
|
import scipy.ndimage as nd
|
|
import skimage.feature as ft
|
|
from skimage.io import imread
|
|
from skimage import data
|
|
|
|
|
|
# settings for LBP
|
|
METHOD = 'uniform'
|
|
P = 16
|
|
R = 2
|
|
|
|
|
|
def kullback_leibler_divergence(p, q):
|
|
p = np.asarray(p)
|
|
q = np.asarray(q)
|
|
filt = np.logical_and(p != 0, q != 0)
|
|
return np.sum(p[filt] * np.log2(p[filt] / q[filt]))
|
|
|
|
|
|
def match(refs, img):
|
|
best_score = 10
|
|
best_name = None
|
|
lbp = ft.local_binary_pattern(img, P, R, METHOD)
|
|
hist, _ = np.histogram(lbp, normed=True, bins=P + 2, range=(0, P + 2))
|
|
for name, ref in refs.items():
|
|
ref_hist, _ = np.histogram(ref, normed=True, bins=P + 2,
|
|
range=(0, P + 2))
|
|
score = kullback_leibler_divergence(hist, ref_hist)
|
|
if score < best_score:
|
|
best_score = score
|
|
best_name = name
|
|
return best_name
|
|
|
|
|
|
brick = data.load('brick.png')
|
|
grass = data.load('grass.png')
|
|
wall = data.load('rough-wall.png')
|
|
|
|
refs = {
|
|
'brick': ft.local_binary_pattern(brick, P, R, METHOD),
|
|
'grass': ft.local_binary_pattern(grass, P, R, METHOD),
|
|
'wall': ft.local_binary_pattern(wall, P, R, METHOD)
|
|
}
|
|
|
|
print match(refs, nd.rotate(brick, angle=30, reshape=False))
|
|
print match(refs, nd.rotate(brick, angle=70, reshape=False))
|
|
print match(refs, nd.rotate(grass, angle=145, reshape=False))
|