OpenCv的连通域操作

由于项目需要,要对图像中的最大连通域进行标定,并且存储。首先需要使用cvFindCountour对边缘进行标定,其实它的原理就是连通域的边缘提取;其次就是对连通域进行大小判断找出最大的连通域;最后当然就是进行Rect并且ROI了。如果有需要可以进行存储。直接上源码吧。

#include "cv.h"
#include "cxcore.h"
#include "highgui.h"
 
int main( int argc, char** argv )
{
 //声明IplImage指针
 IplImage* pImg = cvLoadImage("black.bmp",0);
 IplImage* pContourImg = NULL;
 CvMemStorage * storage = cvCreateMemStorage(0);
 CvSeq * contour = 0;
 CvSeq *contmax = 0;
 int mode = CV_RETR_EXTERNAL;
 cvShowImage( "src", pImg );
 //为轮廓显示图像申请空间
 //3通道图像,以便用彩色显示
 pContourImg = cvCreateImage(cvGetSize(pImg),
  IPL_DEPTH_8U,
  3);
 //copy source image and convert it to BGR image
 cvCvtColor(pImg, pContourImg, CV_GRAY2BGR);
 //查找contour
 cvFindContours( pImg, storage, &contour, sizeof(CvContour),
  mode, CV_CHAIN_APPROX_SIMPLE, cvPoint(0,0));
 //将轮廓画出   
 cvDrawContours(pContourImg, contour,
  CV_RGB(255,0,0), CV_RGB(255, 0, 0),
  2, 2, 8, cvPoint(0,0));
 int area,maxArea = 10;//设面积最大值大于10Pixel
 for(;contour;contour = contour->h_next)
 {
  area = fabs(cvContourArea( contour, CV_WHOLE_SEQ )); //获取当前轮廓面积
  printf("area == %lf\n", area);
  if(area > maxArea)
  {
   contmax = contour;
   maxArea = area;
  }
 }
 CvRect aRect = cvBoundingRect( contmax, 0 );
 cvSetImageROI( pContourImg,aRect);
 //显示图像
 cvShowImage( "contour", pContourImg );
 cvSaveImage("contour.bmp",pContourImg);
 cvWaitKey(0);

 //销毁窗口
 cvDestroyWindow( "src" );
 cvDestroyWindow( "contour" );
 //释放图像
 cvReleaseImage( &pImg );
 cvReleaseImage( &pContourImg );
 cvReleaseMemStorage(&storage);

 return 0;
}

处理前的连通域

OpenCv的连通域操作_第1张图片处理后的连通域
OpenCv的连通域操作_第2张图片

  1. a. 二值化  
  2. b. 得到轮廓的个数  
  3. c. 将面积小于100的轮廓删除  
  4. d. 将宽、高 比例小于1的轮廓删除  
  5. e. 把面积最大的米粒用红色框框画出来  
#include 
#include 
#include 
#include 

#pragma comment(lib, "ml.lib")
#pragma comment(lib, "cv.lib")
#pragma comment(lib, "cvaux.lib")
#pragma comment(lib, "cvcam.lib")
#pragma comment(lib, "cxcore.lib")
#pragma comment(lib, "cxts.lib")
#pragma comment(lib, "highgui.lib")
#pragma comment(lib, "cvhaartraining.lib")
int main( int argc, char** argv )  
{  
	IplImage* src;  
	src=cvLoadImage("black.jpg",CV_LOAD_IMAGE_GRAYSCALE);  
	IplImage* dst = cvCreateImage( cvGetSize(src), 8, 3 );  
	CvMemStorage* storage = cvCreateMemStorage(0);  
	CvSeq* contour = 0;  
	cvThreshold( src, src,120, 255, CV_THRESH_BINARY );//二值化   
	cvNamedWindow( "Source", 1 );  
	cvShowImage( "Source", src );  
	//提取轮廓   
	cvFindContours( src, storage, &contour, sizeof(CvContour), CV_RETR_CCOMP, CV_CHAIN_APPROX_SIMPLE );  
	cvZero( dst );//清空数组   
	CvSeq* _contour =contour;   
	double maxarea=0;  
	double minarea=100;  
	int n=-1,m=0;//n为面积最大轮廓索引,m为迭代索引   
	for( ; contour != 0; contour = contour->h_next )  
	{  

		double tmparea=fabs(cvContourArea(contour));  
		if(tmparea < minarea)   
		{  
			cvSeqRemove(contour,0); //删除面积小于设定值的轮廓   
			continue;  
		}  
		CvRect aRect = cvBoundingRect( contour, 0 );   
		if ((aRect.width/aRect.height)<1)  
		{  
			cvSeqRemove(contour,0); //删除宽高比例小于设定值的轮廓   
			continue;  
		}  
		if(tmparea > maxarea)  
		{  
			maxarea = tmparea;  
			n=m;  
		}  
		m++;  
		//  CvScalar color = CV_RGB( rand()&255, rand()&255, rand()&255 );//创建一个色彩值   
		CvScalar color = CV_RGB( 0, 255,255 );  

		//max_level 绘制轮廓的最大等级。如果等级为0,绘制单独的轮廓。如果为1,绘制轮廓及在其后的相同的级别下轮廓。   
		//如果值为2,所有的轮廓。如果等级为2,绘制所有同级轮廓及所有低一级轮廓,诸此种种。   
		//如果值为负数,函数不绘制同级轮廓,但会升序绘制直到级别为abs(max_level)-1的子轮廓。    
		cvDrawContours( dst, contour, color, color, -1, 1, 8 );//绘制外部和内部的轮廓   
	}  
	contour =_contour; /*int k=0;*/  
	int count=0;  
	for( ; contour != 0; contour = contour->h_next )  
	{  
		count++;  
		double tmparea=fabs(cvContourArea(contour));  
		if (tmparea==maxarea /*k==n*/)  
		{  
			CvScalar color = CV_RGB( 255, 0, 0);  
			cvDrawContours( dst, contour, color, color, -1, 1, 8 );  
		}  
		/*k++;*/  
	}  
	printf("The total number of contours is:%d",count);  
	cvNamedWindow( "Components", 1 );  
	cvShowImage( "Components", dst );  
	cvWaitKey(0);  
	cvDestroyWindow( "Source" );  
	cvReleaseImage(&src);  
	cvDestroyWindow( "Components" );  
	cvReleaseImage(&dst);  
	return 0;  
}  

以下是结果:



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