什么是识别阈【图像处理与识别实验】—— 高斯模糊处理、图像形态处理、形态学操作处理阈值化图像

# ch01_fig1-9~.py
# -*- coding: utf-8 -*-
from PIL import Image
from pylab import *
from scipy.ndimage import filters

# 添加中文字体支持
from matplotlib.font_manager import FontProperties
font = FontProperties(fname=r"c:windowsfontsSimSun.ttc", size=14)

#im = array(Image.open('board.jpeg'))
im = array(Image.open('empire.jpg').convert('L'))
figure()
gray()
axis('off')
subplot(1, 4, 1)
axis('off')
title(u'原图', fontproperties=font)
imshow(im)

# for bi, blur in enumerate([2, 5, 10]):
# im2 = zeros(im.shape)
# im2 = filters.gaussian_filter(im, blur)
# im2 = np.uint8(im2)
# imNum=str(blur)
# subplot(1, 4, 2 + bi)
# axis('off')
# title(u'标准差为'+imNum, fontproperties=font)
# imshow(im2)
# 如果是彩色图像，则分别对三个通道进行模糊

for bi, blur in enumerate([2, 5, 10]):
 im2 = zeros(im.shape)
 for i in range(3):
   im2[:, :, i] = filters.gaussian_filter(im[:, :, i], blur)
 im2 = np.uint8(im2)
 subplot(1, 4,  2 + bi)
 axis('off')
 imshow(im2)

show()