C++利用Opencv實現(xiàn)多個圓形檢測

第C++利用Opencv實現(xiàn)多個圓形檢測主要是利用霍夫圓檢測、面積篩選等完成多個圓形檢測，具體代碼及結果如下。

第一部分是頭文件（common.h）：

#pragmaonce

#includeopencv2/opencv.hpp

#includeopencv2/highgui.hpp

#includeiostream

usingnamespacestd;

usingnamespacecv;

externMatsrc;

voidimageBasicInformation(Matsrc);//圖像基本信息

constMathoughCirclePre(MatsrcPre);//霍夫圓檢測預處理

voidhoughCircle(MatsrcPreHough);//霍夫圓檢測

constMatRectCirclePre(MatsrcPre);//面積篩選擬合圓的預處理

voidAreaCircles(MatAreaInput);//面積篩選擬合圓檢測

第二部分是主函數(shù)：

#include"common.h"

Matsrc;

intmain()

src=imread("1.jpg",1);

if(src.empty())

cout"圖像不存在！"endl;

else

namedWindow("原圖",1);

imshow("原圖",src);

imageBasicInformation(src);

MatsrcPreHough=houghCirclePre(src);

houghCircle(srcPreHough);

MatRectCir=RectCirclePre(src);

AreaCircles(RectCir);

waitKey(0);

destroyAllWindows();

return0；

}

第三部分為霍夫圓檢測函數(shù)（hough.cpp）

主要包括輸出圖像的基本信息函數(shù)：voidimageBasicInformation(Matsrc)

霍夫圓檢測預處理函數(shù)：constMathoughCirclePre(MatsrcPre)

霍夫圓檢測函數(shù)：voidhoughCircle(MatsrcPreHough)

#include"common.h"

MatgraySrc,srcPre;//灰度圖，霍夫檢測預處理，

Matthreshold_grayaSrc;//二值化圖

Materode_threshold_graySrc,dilate_threshold_graySrc;//二值化后腐蝕，二值化后膨脹

voidimageBasicInformation(Matsrc)

intcols=src.cols;

introws=src.rows;

intchannels=src.channels();

cout"圖像寬為："colsendl;

cout"圖像高為："rowsendl;

cout"圖像通道數(shù)："channelsendl;

constMathoughCirclePre(MatsrcPre)

doublehoughCirclePreTime=static_castdouble(getTickCount());

cvtColor(srcPre,graySrc,COLOR_BGR2GRAY);

GaussianBlur(graySrc,graySrc,Size(3,3),2,2);//濾波

threshold(graySrc,threshold_grayaSrc,150,255,1);//二值化

Matelement=getStructuringElement(MORPH_RECT,Size(15,15));

dilate(threshold_grayaSrc,dilate_threshold_graySrc,element);//膨脹

erode(dilate_threshold_graySrc,erode_threshold_graySrc,element);//腐蝕

houghCirclePreTime=((double)getTickCount()-houghCirclePreTime)/getTickFrequency();

cout"霍夫圓預處理時間為："houghCirclePreTime"秒"endl;

returnerode_threshold_graySrc;

voidhoughCircle(MatsrcPreHough)

cout"進入霍夫圓檢測"endl;

vectorVec3fcircles;

HoughCircles(srcPreHough,circles,HOUGH_GRADIENT,1,60,1,35,0,0);

cout"圓的個數(shù)"circles.size()endl;

for(size_ti=0;icircles.size();i++)

Pointcenter(cvRound(circles[i][0]),cvRound(circles[i][1]));

intradius=cvRound(circles[i][2]);

circle(src,center,3,Scalar(0,255,0),-1,8,0);//畫圓心

circle(src,center,radius,Scalar(0,0,255),3,8,0);//畫圓

namedWindow("霍夫檢測結果",0);

imshow("霍夫檢測結果",src);

imwrite("霍夫圓檢測結果.jpg",src);//保存檢測結果

}

第四部分為利用面積篩選擬合圓檢測（AreaCircle.cpp）

主要包括預處理函數(shù)：constMatRectCirclePre(MatsrcPre)

面積篩選擬合圓檢測函數(shù)：voidAreaCircles(MatAreaInput)

#include"common.h"

MatgraySrcArea,thresholdGraySrc;//灰度圖像，二值化圖像

MatdilateThresholdGraySrc,erodeThresholdGraySrc;//二值化后膨脹圖像，膨脹之后的腐蝕圖像

constMatRectCirclePre(MatsrcPre)

cvtColor(srcPre,graySrcArea,COLOR_BGR2GRAY);

GaussianBlur(graySrcArea,graySrcArea,Size(3,3),2,2);

threshold(graySrcArea,thresholdGraySrc,100,255,1);//二值化，閾值要根據(jù)自己的圖像自己調整

Matelement=getStructuringElement(MORPH_RECT,Size(15,15));

dilate(thresholdGraySrc,dilateThresholdGraySrc,element);//膨脹

erode(dilateThresholdGraySrc,erodeThresholdGraySrc,element);//腐蝕

returnerodeThresholdGraySrc;

voidAreaCircles(MatAreaInput)

vectorvectorPointRectContours;

vectorVec4iHierarchy;

findContours(AreaInput,RectContours,Hierarchy,RETR_TREE,CHAIN_APPROX_SIMPLE,Point(0,0));

Matdrawing=Mat::zeros(src.size(),CV_8UC3);

for(inti=0;iRectContours.size();i++)

doublearea=contourArea(RectContours[i]);

coutareaendl;//輸出所有計算出來的面積，方便下一步設置閾值

if(area15000area100000)//根據(jù)上一步計算的閾值設置范圍

drawContours(drawing,RectContours,i,Scalar(0,255,0),2,8,Hierarchy,0,Point());

RotatedRectRect=fitEllipse(RectContours[i]);

circle(src,Rect.center,2,Scalar(0,255,0),2,8,0);//在原圖畫出圓心

ellipse(sr