Python |图像处理中的形态运算（开放）|S1

形态学操作用于提取在区域形状表示和描述中有用的图像成分。形态学操作是一种基于图像形状的基本操作。它通常在二值图像上执行。它需要两个数据源，一个是输入图像，另一个是结构化组件。形态操作符以输入图像和结构组件作为输入，然后使用集合操作符组合这些元素。输入图像中的对象根据图像形状的属性进行处理，这些属性被编码在结构化组件中。

开放与侵蚀相似，因为它倾向于从前景像素区域的边缘去除明亮的前景像素。操作员的作用是在剔除前景像素的其他区域的同时，保护与结构组件相似的前景区域，或者完全包含结构组件的前景区域。打开操作用于去除图像中的内部噪声。

语法：cv2.morphologyEx(image, cv2.MORPH_OPEN, kernel)参数：
-> image：输入图像数组。
-> cv2.MORPH_OPEN：应用形态打开操作。
->kernel：结构元素。

以下是解释开放形态操作的Python代码-

# Python programe to illustrate
# Opening morphological operation
# on an image
  
# organizing imports  
import cv2  
import numpy as np  
  
# return video from the first webcam on your computer.  
screenRead = cv2.VideoCapture( 0 )
  
# loop runs if capturing has been initialized.
while ( 1 ):
     # reads frames from a camera
     _, image = screenRead.read()
      
     # Converts to HSV color space, OCV reads colors as BGR 
     # frame is converted to hsv
     hsv = cv2.cvtColor(image, cv2.COLOR_BGR2HSV)
      
     # defining the range of masking
     blue1 = np.array([ 110 , 50 , 50 ])
     blue2 = np.array([ 130 , 255 , 255 ])
      
     # initializing the mask to be
     # convoluted over input image
     mask = cv2.inRange(hsv, blue1, blue2)
  
     # passing the bitwise_and over
     # each pixel convoluted
     res = cv2.bitwise_and(image, image, mask = mask)
      
     # defining the kernel i.e. Structuring element
     kernel = np.ones(( 5 , 5 ), np.uint8)
      
     # defining the opening function 
     # over the image and structuring element
     opening = cv2.morphologyEx(mask, cv2.MORPH_OPEN, kernel)
     
     # The mask and opening operation
     # is shown in the window 
     cv2.imshow( 'Mask' , mask)
     cv2.imshow( 'Opening' , opening)
      
     # Wait for 'a' key to stop the program 
     if cv2.waitKey( 1 ) & 0xFF = = ord ( 'a' ):
         break
  
# De-allocate any associated memory usage  
cv2.destroyAllWindows()
  
# Close the window /Release webcam 
screenRead.release()

输入框：