How to perform three-channel Canny edge detection on color images

This article mainly records how to perform three-channel Canny edge detection on color images.

How to perform three-channel Canny edge detection on color images
0. Main steps
1. Separate the color image into 3-channel images
2. Grayscale image to achieve Canny edge detection
3. Display edge detection results

0. Main steps

The three-channel Canny edge detection of the color image mainly includes the following two steps:
(1) Separate the color image into images of three channels;
(2) Perform Canny edge detection on the images of the three channels;
(3 ) to show the edge detection results.

1. Separate the color image into 3-channel images

Separate the color image Airplane into three channel images, Airplane_B.jpg, Airplane_G.jpg, Airplane_R.jpg. The specific code is:

# coding ：UTF-8
# 文件功能： 代码实现彩色图像三通道分别提取的功能
# 开发人员： XXX
# 开发时间： 2022/6/11 6:20 下午
# 文件名称： Three_Channel_Extraction_of_Color_Images.py
# 开发工具： PyCharm


# 当采用CV2时，读取到的彩色图像的三通道顺序为：BGR
# 本程序是实现将一个彩色图像分离出3个通道的图像，然后分别保存为3张图像，并用Orinal_Canny_Edge_Detection.py实现边缘检测。

import cv2
import numpy as np

img = cv2.imread('image/Airplane.tiff')  # 读取图像

# 显示彩色图像
cv2.imshow("img", img)
cv2.waitKey(0)

gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
# 显示灰度图像
cv2.imshow("gray", gray)
cv2.waitKey(0)

# 得到图像的大小
rows, cols, _ = img.shape
print(rows, cols)

# 初始化一个大小一样的图像，元素均初始化为0
created = np.zeros((rows, cols))

# for in 语句，遍历数组，但不能修改数组
for i in img:
    for j in i:
        #print(j)
        pass

# 给数组赋值
for i in range(0, rows):
    for j in range(0, cols):
        created[i, j] = img[i, j, 2]   # 第3个参数，可以是0，1，2，分别表示B,G,R三个通道

print(created.shape)  # 输出创建图像的大小
# 必须加上下面这一条语句，否则无法正确显示图像
created = created.astype(np.uint8)  # 转换数据类型，才能正确的显示图像
cv2.imshow('created', created)
cv2.imwrite('image/Airplane_R.jpg', created)
cv2.waitKey(0)

2. Grayscale image to achieve Canny edge detection

The images of the three channels are subjected to Canny edge detection. The specific code is as follows:

# coding ：UTF-8
# 文件功能： 代码实现最简单的Canny edge detection边缘检测的功能
# 开发人员： XXX
# 开发时间： 2022/6/11 5:18 下午
# 文件名称： Orinal_Canny_Edge_Detection.py
# 开发工具： PyCharm


import cv2
import numpy as np

from PIL import Image

lower = 30  # 最小阈值
upper = 70  # 最大阈值

img_path = 'image/Airplane_R.jpg'   # 指定测试图像路径

gray = cv2.imread(img_path, 0)   # 读取灰度图像
edge = cv2.Canny(gray, lower, upper)   # Canny 图像边缘检测

contrast = np.concatenate([edge, gray], 1)   # 图像拼接
Image.fromarray(contrast).save('image/Airplane_R_edge.png', format='PNG')   # 保存图像