OpenCV：边缘检测

ゞ浴缸里的玫瑰 2022-10-01 10:54 230阅读 0赞

*  使用OpenCV自带函数完成边缘检测

import cv2
    import numpy as np
    import random
    
    img = cv2.imread('test.png',1)
    imgInfo = img.shape
    height = imgInfo[0]
    width = imgInfo[1]
    cv2.imshow('image0',img)
    
    gray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)
    imgG = cv2.GaussianBlur(gray,(3,3),0)
    dst = cv2.Canny(img,50,50)
    
    cv2.imshow('image1',dst)
    cv2.waitKey(0)

对比效果如下：  
![在这里插入图片描述][watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L2x0MzI2MDMwNDM0_size_16_color_FFFFFF_t_70]

*  自己编写代码完成边缘检测

import cv2
    import numpy as np
    import random
    import math
    
    img = cv2.imread('test.png',1)
    imgInfo = img.shape
    height = imgInfo[0]
    width = imgInfo[1]
    cv2.imshow('image0',img)
    
    gray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)
    dst = np.zeros((height,width,1),np.uint8)
    for i in range(height-2):
        for j in range(width-2):
            gy = gray[i,j]*1+gray[i,j+1]*2+gray[i,j+2]*1-gray[i+2,j]*1-gray[i+2,j+1]*2-gray[i+2,j+2]*1
            gx = gray[i,j]*1+gray[i+1,j]*2+gray[i+2,j]*1-gray[i,j+2]*1-gray[i+1,j+2]*2-gray[i+2,j+2]*1
            grad = math.sqrt(gx*gx+gy*gy)
            if grad>50:
                dst[i,j] = 255
            else:
                dst[i,j] = 0
    
    cv2.imshow('image1',dst)
    cv2.waitKey(0)

对比效果如下：  
![在这里插入图片描述][watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L2x0MzI2MDMwNDM0_size_16_color_FFFFFF_t_70 1]

[watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L2x0MzI2MDMwNDM0_size_16_color_FFFFFF_t_70]: /images/20220118/bf68037ba5844afc98b1dc6aa9045ffa.png
[watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L2x0MzI2MDMwNDM0_size_16_color_FFFFFF_t_70 1]: /images/20220118/e8f2ddf512c94d21864d1de9cb86c2c4.png