Halcon实例转OpenCV--低对比度图像中提取圆形轮廓(附源码)

导读

本文主要介绍一个在低对比度图像中提取圆形轮廓的实例，并将Halcon实现转为OpenCV。

实例来源

Halcon例程dyn_threshold.hdev--动态阈值算子使用实例。

原图：

Halcon实现效果：

OpenCV实现步骤与代码

实现步骤:

【1】dyn_threshold操作替代--均值滤波+图像差分+阈值提取

【2】圆形结构元素闭运算+开运算

【3】轮廓查找+最小外接圆

【4】标注结果：圆心+外圆轮廓

逐步效果演示与代码:

完整源码：

#--公众号：OenCV与AI深度学习
#--Author:Color Space
import numpy as np

import cv2

font=cv2.FONT_HERSHEY_SIMPLEX

img = cv2.imread('embossed_01.png')

cv2.imshow('src', img)

gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)

blur = cv2.blur(gray, (50,50))

cv2.imshow('blur', blur)

diff = cv2.absdiff(gray, blur)

cv2.imshow('diff', diff)

ret,thres = cv2.threshold(diff,15,255,cv2.cv2.THRESH_BINARY)

cv2.imshow('thres', thres)

k1 = np.zeros((19, 19),np.uint8)
cv2.circle(k1,(9,9),9,(1,1,1),-1,cv2.LINE_AA)

closing = cv2.morphologyEx(thres, cv2.MORPH_CLOSE, k1, None, None, 1)#闭运算
cv2.imshow('closing',closing)

k2 = np.zeros((13, 13),np.uint8)
cv2.circle(k2,(6,6),6,(1,1,1),-1,cv2.LINE_AA)

opening = cv2.morphologyEx(closing, cv2.MORPH_OPEN, k2, None, None, 1)#闭运算
cv2.imshow('opening',opening)

contours,hierarchy = cv2.findContours(opening, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_NONE)
count = 0
for cnt in contours:
  center,radius = cv2.minEnclosingCircle(cnt)
  if radius < 5:
    continue
  count = count + 1
  cv2.circle(img,(int(center[0]),int(center[1])),int(radius),(0,255,0),2)
  cv2.drawMarker(img,(int(center[0]),int(center[1])),(0,0,255),
                     cv2.MARKER_CROSS, 15,1,8)
strCount = "count = %d" % count
cv2.putText(img,strCount,(10,30),font,1.0,(255,0,0),2)

cv2.imshow('result', img)
cv2.imwrite('result.jpg', img)

cv2.waitKey(0)
cv2.destroyAllWindows()

原图：

均值滤波结果图：

差分图像：

阈值结果：

闭运算结果：

开运算结果：

最终结果：

更多视觉图像处理相关内容，请点击关注：OpenCV与AI深度学习。

​