对于简单的场景管用，复杂的场景效果不明显。

 方法一：基于LoG算子的圆斑检测。

这是常用的斑点检测方法，可参考http://doc.okbase.net/ronny/archive/102540.html。

此方法的问题是，图像中不是圆形的斑点也会检测出来，还需要进一步的判断，这使得算法的效率不高。

/* SimpleBlobDetector::Params params; //阈值控制

params.minThreshold = 10; params.maxThreshold = 200; //像素面积大小控制

params.filterByArea = true; params.minArea = 1000; //形状（凸）

params.filterByCircularity = false; params.minCircularity = 0.7; //形状（凹）

params.filterByConvexity = true; params.minConvexity = 0.9; //形状（园）

params.filterByInertia = false; params.minInertiaRatio = 0.5; */

LoG检测

利用高斯拉普拉斯LOG算子检测图像斑点较DoH，Harris和其它点检测方法稳定性更好，抗图像中噪声的能力更强 

  

   

    

     

    
    

     

      #!/usr/bin/env python
     
    
   

    

     

    
    

     

      # -*- coding: utf-8 -*-
     
    
   

    

     

    
    

     
 
     
    
   

    

     

    
    

     

      # Standard imports
     
    
   

    

     

    
    

     

      import os
     
    
   

    

     

    
    

     
 
     
    
   

    

     

    
    

     

      import cv2
     
    
   

    

     

    
    

     

      import numpy as np
     
    
   

    

     

    
    

     
 
     
    
   

    

     

    
    

     
 
     
    
   

    

     

    
    

     

      path=r"Images/"
     
    
   

    

     

    
    

     
 
     
    
   

    

     

    
    

     

      files=os.listdir(path)
     
    
   

    

     

    
    

     

      for file in files:
     
    
   

    

     

    
    

     
 
     
    
   

    

     

    
    

     
 # Read image
     
    
   

    

     

    
    

     

       im = cv2.imread(path+file)
     
    
   

    

     

    
    

     

       im_o = cv2.resize(im, (800,600))
     
    
   

    

     

    
    

     
 
     
    
   

    

     

    
    

     

       im_gauss = cv2.cvtColor(im_o, cv2.COLOR_RGB2GRAY)
     
    
   

    

     

    
    

     

       im_gauss = cv2.GaussianBlur(im_gauss, (3, 3), 0)
     
    
   

    

     

    
    

     

       ret, im = cv2.threshold(im_gauss, 30, 255, 0)
     
    
   

    

     

    
    

     

       cv2.imshow("o", im)
     
    
   

    

     

    
    

     
 # Setup SimpleBlobDetector parameters.
     
    
   

    

     

    
    

     

       params = cv2.SimpleBlobDetector_Params()
     
    
   

    

     

    
    

     
 
     
    
   

    

     

    
    

     
 # Change thresholds
     
    
   

    

     

    
    

     

       params.minThreshold = 10
     
    
   

    

     

    
    

     

       params.maxThreshold = 200
     
    
   

    

     

    
    

     
 
     
    
   

    

     

    
    

     
 # Filter by Area.
     
    
   

    

     

    
    

     

       params.filterByArea = True
     
    
   

    

     

    
    

     

       params.minArea = 16
     
    
   

    

     

    
    

     
 
     
    
   

    

     

    
    

     
 # Filter by Circularity
     
    
   

    

     

    
    

     

       params.filterByCircularity = True
     
    
   

    

     

    
    

     

       params.minCircularity = 0.3
     
    
   

    

     

    
    

     
 
     
    
   

    

     

    
    

     
 # Filter by Convexity
     
    
   

    

     

    
    

     

       params.filterByConvexity = True
     
    
   

    

     

    
    

     

       params.minConvexity = 0.57
     
    
   

    

     

    
    

     
 
     
    
   

    

     

    
    

     
 # Filter by Inertia
     
    
   

    

     

    
    

     

       params.filterByInertia = True
     
    
   

    

     

    
    

     

       params.minInertiaRatio = 0.01
     
    
   

    

     

    
    

     
 
     
    
   

    

     

    
    

     
 # Create a detector with the parameters
     
    
   

    

     

    
    

     

       ver = (cv2.__version__).split('.')
     
    
   

    

     

    
    

     
 if int(ver[0]) < 3:
     
    
   

    

     

    
    

     

       detector = cv2.SimpleBlobDetector(params)
     
    
   

    

     

    
    

     
 else:
     
    
   

    

     

    
    

     

       detector = cv2.SimpleBlobDetector_create(params)
     
    
   

    

     

    
    

     
 
     
    
   

    

     

    
    

     
 # Detect blobs.
     
    
   

    

     

    
    

     

       keypoints = detector.detect(im)
     
    
   

    

     

    
    

     
 
     
    
   

    

     

    
    

     
 # Draw detected blobs as red circles.
     
    
   

    

     

    
    

     
 # cv2.DRAW_MATCHES_FLAGS_DRAW_RICH_KEYPOINTS ensures
     
    
   

    

     

    
    

     
 # the size of the circle corresponds to the size of blob
     
    
   

    

     

    
    

     
 
     
    
   

    

     

    
    

     

       im_with_keypoints = cv2.drawKeypoints(im_o, keypoints, np.array([]), (0, 0, 255),cv2.DRAW_MATCHES_FLAGS_DRAW_RICH_KEYPOINTS)
     
    
   

    

     

    
    

     
 
     
    
   

    

     

    
    

     
 # Show blobs
     
    
   

    

     

    
    

     

       cv2.imshow("Keypoints", im_with_keypoints)
     
    
   

    

     

    
    

     

       cv2.waitKey(0)
     
    
   

    

     

    
    

     
 
     
    
  
 

文章来源: blog.csdn.net，作者：网奇，版权归原作者所有，如需转载，请联系作者。

原文链接：blog.csdn.net/jacke121/article/details/96865498