python的数字图像处理学习（3）

高级滤波：

 from skimage import data,color,data_dir
 import matplotlib.pyplot as plt
 from skimage.morphology import disk
 import skimage.filters.rank as sfr
 img =color.rgb2gray(data.camera())
 auto =sfr.autolevel(img, disk(5))  #半径为5的圆形滤波器
 plt.figure('filters',figsize=(8,8))
 plt.subplot(121)
 plt.imshow(img,plt.cm.gray)
 plt.subplot(122)
 plt.imshow(auto,plt.cm.gray)
 data_dir

高级滤波.....

 from skimage import data,color
 import matplotlib.pyplot as plt
 from skimage.morphology import disk
 import skimage.filters.rank as sfr
 img =color.rgb2gray(data.camera())
 auto =sfr.bottomhat(img, disk(5))  #半径为5的圆形滤波器
 auto1 =sfr.tophat(img, disk(5))  #半径为5的圆形滤波器
 plt.figure('filters',figsize=(12,12))
 plt.subplot(131)
 plt.imshow(img,plt.cm.gray)
 plt.subplot(132)
 plt.imshow(auto,plt.cm.gray)
 plt.subplot(133)
 plt.imshow(auto1,plt.cm.gray)

提取轮廓....

 import numpy as np
 import matplotlib.pyplot as plt
 from skimage import measure,draw,data,filters
 #生成二值测试图像
 img=data.page()
 thresh = filters.threshold_isodata(img)
 img1 = (img <= thresh)*1.0   #根据阈值进行分割
 #检测所有图形的轮廓
 img2 = img1[:,:]
 contours = measure.find_contours(img1, 0.5)
 #绘制轮廓
 fig, (ax0,ax1,ax2) = plt.subplots(1,3,figsize=(15,15))
 ax0.imshow(img,plt.cm.gray)
 ax1.imshow(img1,plt.cm.gray)
 ax2.imshow(img2,plt.cm.gray)    #enumerate索引序列
 for n, contour in enumerate(contours):
     ax2.plot(contour[:, 1], contour[:, 0], linewidth=1)
 plt.show()

提取轮廓..............

 import matplotlib.pyplot as plt
 from skimage import measure,data,color
 img=color.rgb2gray(data.horse())
 contours = measure.find_contours(img, 0.5)
 fig, axes = plt.subplots(1,2,figsize=(8,8))
 ax0, ax1= axes.ravel()
 ax0.imshow(img,plt.cm.gray)
 rows,cols=img.shape
 ax1.axis([0,rows,cols,0])
 for n, contour in enumerate(contours):
     ax1.plot(contour[:, 1], contour[:, 0], linewidth=1)
 ax1.axis('image')
 plt.show()

凸包............

import matplotlib.pyplot as plt
from skimage import data,color,morphology
img=color.rgb2gray(data.horse())
img=(img<0.5)*1
chull = morphology.convex_hull_image(img)
fig, axes = plt.subplots(1,2,figsize=(8,8))
ax0, ax1= axes.ravel()
ax0.imshow(img,plt.cm.gray)
ax1.imshow(chull,plt.cm.gray)

多个凸包.....................................................................................

 import matplotlib.pyplot as plt
 from skimage import data,color,morphology,feature
 img=color.rgb2gray(data.coins())
 edgs=feature.canny(img, sigma=3, low_threshold=10, high_threshold=50)
 chull = morphology.convex_hull_object(edgs)

 #绘制轮廓
 fig, axes = plt.subplots(1,2,figsize=(8,8))
 ax0, ax1= axes.ravel()
 ax0.imshow(edgs,plt.cm.gray)
 ax0.set_title('many objects')
 ax1.imshow(chull,plt.cm.gray)
 ax1.set_title('convex_hull image')
 plt.show()

看不懂也写不下去了...