在Python中使用 OpenCV 进行实时边缘检测Canny边缘检测方法

给出的程序的目标是实时执行图像的边缘检测。在本文中，流行的 canny 边缘检测算法用于检测图像中的各种边缘。 OpenCV 有内置函数cv2.Canny()，它将我们的输入图像作为第一个参数，并将其孔径大小（最小值和最大值）作为最后两个参数。这是一个如何在Python中检测边缘的简单示例。下载要求的步骤如下：

1. 下载Python 2.7.x 版本、numpy 和 OpenCV 2.7.x 或 3.1.0 版本。检查您的 Windows 32 位或 64 位是否兼容并相应安装。
2. 确保 numpy 在你的Python中运行，然后尝试安装 opencv。

执行

Python

# OpenCV program to perform Edge detection in real time
# import libraries of python OpenCV
# where its functionality resides
import cv2
 
# np is an alias pointing to numpy library
import numpy as np
 
 
# capture frames from a camera
cap = cv2.VideoCapture(0)
 
 
# loop runs if capturing has been initialized
while(1):
 
    # reads frames from a camera
    ret, frame = cap.read()
 
    # converting BGR to HSV
    hsv = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV)
     
    # define range of red color in HSV
    lower_red = np.array([30,150,50])
    upper_red = np.array([255,255,180])
     
    # create a red HSV colour boundary and
    # threshold HSV image
    mask = cv2.inRange(hsv, lower_red, upper_red)
 
    # Bitwise-AND mask and original image
    res = cv2.bitwise_and(frame,frame, mask= mask)
 
    # Display an original image
    cv2.imshow('Original',frame)
 
    # finds edges in the input image and
    # marks them in the output map edges
    edges = cv2.Canny(frame,100,200)
 
    # Display edges in a frame
    cv2.imshow('Edges',edges)
 
    # Wait for Esc key to stop
    k = cv2.waitKey(5) & 0xFF
    if k == 27:
        break
 
 
# Close the window
cap.release()
 
# De-allocate any associated memory usage
cv2.destroyAllWindows()

输出： 参考：

• http://docs.opencv.org/2.4/doc/tutorials/imgproc/imgtrans/canny_detector/canny_detector.html
• http://docs.opencv.org/trunk/da/d22/tutorial_py_canny.html
• https://en.wikipedia.org/wiki/Canny_edge_detector
• http://www.ijcsmc.com/docs/papers/July2013/V2I7201329.pdf