image lbp transform: http://homeway.me/2017/05/04/pattern-writer-identify/

lbp.py

#!/usr/bin/env python
# -*- coding: utf-8 -*-

__author__ = 'homeway'
__email__ = '[email protected]'
__copyright__   = 'Copyright © 2017/05/08, homeway'

import numpy as np
import cv2
from matplotlib import pyplot as plt

def thresholded(center, pixels):
	out = []
		for a in pixels:
	if a < center:
		out.append(0)
	else:
		out.append(1)
	return out

def get_pixel(pixel_list, idx, idy, default = 0):
	try:
		return pixel_list[idx, idy]
	except IndexError:
		return default

def show(img, lbp_img):
	plt.figure(figsize = (8, 8))
	plt.subplot(221)
	plt.title("original image")
	plt.imshow(img, cmap=plt.cm.Greys_r)

	plt.subplot(222)
	plt.title("LBP transform image")
	plt.imshow(lbp_img, cmap=plt.cm.Greys_r)
	
	plt.subplot(223)
	(hist, bins) = np.histogram(img.flatten(), 256, [0, 256])
	cdf = hist.cumsum()
	cdf_normalized = cdf * hist.max() / cdf.max()
	plt.plot(cdf_normalized, color = 'b')
	plt.hist(img.flatten(), 256, [0, 256], color = 'r')
	plt.xlim([0, 256])
	plt.legend(('cdf', 'histogram'), loc = 'upper left')

	plt.show()

def main(fpath):
	img = cv2.imread(fpath, cv2.IMREAD_GRAYSCALE)
	lbp_img = cv2.imread(fpath, cv2.IMREAD_GRAYSCALE)

	offset = [(-1, -1), (0, -1), (1, -1), (1, 0), (-1, 0), (-1, 1), (1, 1), (0, 1)]
	for x in range(len(img)):
		for y in range(len(img[x])):
			matrix = []
			for z in range(len(offset)):
				matrix.append(get_pixel(img, x + offset[z][0], y + offset[z][1]))
			center = img[x, y]
			# get thresholded 0101 value
			values = thresholded(center, matrix)
			weights = [1, 2, 4, 8, 16, 32, 64, 128]
			# add thresholded weight
			res = 0
			for a in range(len(values)):
			    res += weights[a] * values[a]
			lbp_img.itemset((x,y), res)
	show(img, lbp_img)
	
if __name__ == '__main__':
	main(r'/path/to/img')