在opencv中应用sobel和laplacian滤波器后图像的边缘检测

Question

我正在对图像进行图像分割，但是我想做的是在应用Laplacian和Sobel滤镜的并集之后，使用Canny边缘检测对图像进行图像分割。是的，我已经完成了值的归一化并将图像转换为灰度。我无法在最终图像或sob中进行边缘检测。 以下错误

错误：OpenCV（4.2.0） C：\ projects \ opencv-python \ opencv \ modules \ imgproc \ src \ canny.cpp：829： 错误：（-215：声明失败）_src.depth（）==函数中的CV_8U 'cv :: Canny'

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

path=r"C:\Users\MACHINE\Desktop\3.jpg"

img=cv.imread(path)
img=cv.cvtColor(img,cv.COLOR_RGB2GRAY)
laplacian=cv.Laplacian(img,cv.CV_64F)
laplacian=(laplacian-laplacian.min())/(laplacian.max()-laplacian.min())
sobelx = cv.Sobel(img,cv.CV_64F,1,0,ksize=5)
sobely = cv.Sobel(img,cv.CV_64F,0,1,ksize=5)
sob=(sobelx+sobely) 
sob=(sob-sob.min())/(sob.max()-sob.min()) # taking care of negative values and values out of range
final=sob+laplacian
final=(final-final.min())/(final.max()-final.min()) 
print(sob.shape)
#canny1=cv.Canny(sob,100,200) #thise code is showing error on sob .but works perfectly fine on orginal image



plt.subplot(2,2,1)    
plt.imshow(canny1,cmap='gray')
plt.subplot(2,2,2)    
plt.imshow(sob,cmap='gray')
plt.subplot(2,2,3)    
plt.imshow(final,cmap='gray')

Answer 1

传递给Canny的图像必须为uint8，但是您的sob，laplacian和final为float64，范围为0 -1。

您可以乘以255，然后转换为uint8：

canny1 = cv.Canny(np.uint8(sob * 255) ,100, 200)

或：

canny1 = cv.Canny(cv.convertScaleAbs(sob * 255) ,100, 200)

Answer 2

错误代码表明您应该首先将图像转换为CV_8U深度格式。 sob的格式为CV_64F。所以这应该工作：

sob = np.uint8(sob*255)
canny1=cv.Canny(sob,100,200)    #after that you can call Canny