Python|图像处理中的形态学操作（梯度）|第 3 组

在之前的文章中，指定了打开操作和关闭操作。在本文中，阐述了另一种形态学运算，即Gradient 。它用于生成图像的轮廓。渐变有两种类型，内部渐变和外部渐变。内部渐变增强了比背景更亮的对象的内部边界和比背景暗的对象的外部边界。对于二值图像，内部梯度会生成前景图像对象内部边界的掩码。

Syntax: cv2.morphologyEx(image, cv2.MORPH_GRADIENT, kernel)
Parameters:
-> image: Input Image array.
-> cv2.MORPH_GRADIENT: Applying the Morphological Gradient operation.
-> kernel: Structuring element.

编程需要懂一点英语

下面是解释梯度形态学运算的Python代码——

Python3

# Python program to illustrate
# Gradient morphological operation
# on input frames
 
# 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 gradient function
    # over the image and structuring element
    gradient = cv2.morphologyEx(mask, cv2.MORPH_GRADIENT, kernel)
    
    # The mask and closing operation
    # is shown in the window
    cv2.imshow('Gradient', gradient)
     
    # 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()

结果：

输出图像帧显示在蓝皮书和左上角的蓝色对象上生成的轮廓。