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图像侵蚀

用于消除小的白色噪声

import cv2import numpy as npfrom matplotlib import pyplot as pltimg = cv2.imread('number.jpg')kernel = np.ones((5,5),np.uint8)erosion = cv2.erode(img,kernel,iterations= 1)plt.subplot(121),plt.imshow(img),plt.title('original'),plt.xticks([]),plt.yticks([])plt.subplot(122),plt.imshow(erosion),plt.title('erosion'),plt.xticks([]),plt.yticks([])plt.show()

图片扩展 与侵蚀相反

import cv2import numpy as npfrom matplotlib import pyplot as pltimg = cv2.imread('number.jpg')kernel = np.ones((5,5),np.uint8)erosion = cv2.dilate(img,kernel,iterations= 1)plt.subplot(121),plt.imshow(img),plt.title('original'),plt.xticks([]),plt.yticks([])plt.subplot(122),plt.imshow(erosion),plt.title('dilate'),plt.xticks([]),plt.yticks([])plt.show()

开运算 向侵蚀后扩展，用于消除噪音

import cv2import numpy as npfrom matplotlib import pyplot as pltimg = cv2.imread('number.jpg')kernel = np.ones((5,5),np.uint8)erosion = cv2.morphologyEx(img,cv2.MORPH_OPEN,kernel)plt.subplot(121),plt.imshow(img),plt.title('original'),plt.xticks([]),plt.yticks([])plt.subplot(122),plt.imshow(erosion),plt.title('openning'),plt.xticks([]),plt.yticks([])plt.show()

闭运算 与开运算相反

import cv2import numpy as npfrom matplotlib import pyplot as pltimg = cv2.imread('number.jpg')kernel = np.ones((5,5),np.uint8)erosion = cv2.morphologyEx(img,cv2.MORPH_CLOSE,kernel)plt.subplot(121),plt.imshow(img),plt.title('original'),plt.xticks([]),plt.yticks([])plt.subplot(122),plt.imshow(erosion),plt.title('close'),plt.xticks([]),plt.yticks([])plt.show()

形态学梯度 利用对图像的膨胀和腐蚀的组合使用，从而提取了物体的轮廓

import cv2import numpy as npfrom matplotlib import pyplot as pltimg = cv2.imread('number.jpg')kernel = np.ones((5,5),np.uint8)erosion = cv2.morphologyEx(img,cv2.MORPH_GRADIENT,kernel)plt.subplot(121),plt.imshow(img),plt.title('original'),plt.xticks([]),plt.yticks([])plt.subplot(122),plt.imshow(erosion),plt.title('gradient'),plt.xticks([]),plt.yticks([])plt.show()

顶帽 礼帽指的是原始图像与其进行开运算后的图像进行一个差，对于差别之处显示其原有图色

import cv2import numpy as npfrom matplotlib import pyplot as pltimg = cv2.imread('number.jpg')kernel = np.ones((5,5),np.uint8)openning = cv2.morphologyEx(img,cv2.MORPH_OPEN,kernel)tophat = cv2.morphologyEx(img,cv2.MORPH_TOPHAT,kernel)plt.subplot(131),plt.imshow(img),plt.title('original'),plt.xticks([]),plt.yticks([])plt.subplot(132),plt.imshow(openning),plt.title('openning'),plt.xticks([]),plt.yticks([])plt.subplot(133),plt.imshow(tophat),plt.title('tophat'),plt.xticks([]),plt.yticks([])plt.show()

黑帽 黑帽指的是原始图像与其进行闭运算后的图像进行一个差，对于差别之处显示原有图色的反颜色

import cv2import numpy as npfrom matplotlib import pyplot as pltimg = cv2.imread('number.jpg')kernel = np.ones((5,5),np.uint8)close = cv2.morphologyEx(img,cv2.MORPH_CLOSE,kernel)blackhat = cv2.morphologyEx(img,cv2.MORPH_BLACKHAT,kernel)plt.subplot(131),plt.imshow(img),plt.title('original'),plt.xticks([]),plt.yticks([])plt.subplot(132),plt.imshow(close),plt.title('close'),plt.xticks([]),plt.yticks([])plt.subplot(133),plt.imshow(blackhat),plt.title('blackhat'),plt.xticks([]),plt.yticks([])plt.show()

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