机器视觉——Sobel&Scharry&Laplacian

是通过计算图像梯度来得出边缘的算法.

具体见注释

'''
Created on 2023年3月20日

@author: Administrator
'''
import cv2 
import matplotlib.pyplot as plt
import numpy as np 
import os 
from PIL import Image
import pylab
from dill.tests.test_mixins import fx
 
os.chdir('D:/大学资料/计算机视觉/第2-7章笔记课件') #此处路径中可以有中文字符
img=cv2.imread('pie.png',cv2.IMREAD_GRAYSCALE);
cv2.imshow("img",img);
cv2.waitKey();
cv2.destroyAllWindows();

def cv_show(img,name):
    cv2.imshow(name,img);
    cv2.waitKey();
    cv2.destroyAllWindows();
    
sobelx=cv2.Sobel(img,cv2.CV_64F,1,0,ksize=3);
#dx为1说明算的是水平的梯度
cv_show(sobelx,'sobelx');
#右边减左边，右半段梯度为负数，默认截断了，所以只显示了左边的边界
sobelx=cv2.Sobel(img,cv2.CV_64F,1,0,ksize=3);
sobelx=cv2.convertScaleAbs(sobelx)#将结果取绝对值
cv_show(sobelx,'sobelx');

#在算一次竖直的梯度
sobely=cv2.Sobel(img,cv2.CV_64F,0,1,ksize=3);
sobely=cv2.convertScaleAbs(sobely)#将结果取绝对值
cv_show(sobely,'sobely');

#分别计算x和y，再求和
sobelxy=cv2.addWeighted(sobelx,0.5,sobely,0.5,0);
cv_show(sobelxy,'sobelxy');

#若直接计算xy，可能效果不太好
sobelxy=cv2.Sobel(img,cv2.CV_64F,1,1,ksize=3);
sobelxy=cv2.convertScaleAbs(sobelxy)#将结果取绝对值
cv_show(sobelxy,'sobelxy');

#读入图片lena,计算边界
img=cv2.imread('lena.jpg',cv2.IMREAD_GRAYSCALE)
cv_show(img,'img');

sobelx=cv2.Sobel(img,cv2.CV_64F,1,0,ksize=3);
sobelx=cv2.convertScaleAbs(sobelx)#将结果取绝对值
cv_show(sobelx,'sobelx');

sobely=cv2.Sobel(img,cv2.CV_64F,0,1,ksize=3);
sobely=cv2.convertScaleAbs(sobely)#将结果取绝对值
cv_show(sobely,'sobely');

sobelxy=cv2.addWeighted(sobelx,0.5,sobely,0.5,0);
cv_show(sobelxy,'sobelxy');

sobelxy=cv2.Sobel(img,cv2.CV_64F,1,1,ksize=3);
sobelxy=cv2.convertScaleAbs(sobelxy)#将结果取绝对值
cv_show(sobelxy,'sobelxy');


img=cv2.imread('lena.jpg',cv2.IMREAD_GRAYSCALE)
cv_show(img,'img');
#sobel算子
sobelx=cv2.Sobel(img,cv2.CV_64F,1,0,ksize=3);
sobelx=cv2.convertScaleAbs(sobelx)#将结果取绝对值
sobely=cv2.Sobel(img,cv2.CV_64F,0,1,ksize=3);
sobely=cv2.convertScaleAbs(sobely)#将结果取绝对值
sobelxy=cv2.addWeighted(sobelx,0.5,sobely,0.5,0);

#Scharr算子
scharrx=cv2.Scharr(img,cv2.CV_64F,1,0)
scharry=cv2.Scharr(img,cv2.CV_64F,0,1)
scharrx=cv2.convertScaleAbs(scharrx)
scharry=cv2.convertScaleAbs(scharry)
scharrxy=cv2.addWeighted(scharrx,0.5,scharry,0.5,0);

#laplacian算子
laplacian=cv2.Laplacian(img,cv2.CV_64F)
laplacian=cv2.convertScaleAbs(laplacian)

res=np.hstack((sobelxy,scharrxy,laplacian));
cv_show(res,'res')