今天在弄一个查找连通的最大面积的问题。
要把图像弄成黑底,白字,这样才可以正确找到。
然后调用下边的方法:
RETR_CCOMP:提取所有轮廓,并将轮廓组织成双层结构(two-level hierarchy),顶层为连通域的外围边界,次层位内层边界
#include <opencv2/imgproc.hpp
#include <opencv2/highgui.hpp
using namespace cv;
using namespace std;
int main( int argc, char** argv )
{
Mat src = imread( argv[1] );
int largest_area=0;
int largest_contour_index=0;
Rect bounding_rect;
Mat thr;
cvtColor( src, thr, COLOR_BGR2GRAY ); //Convert to gray
threshold( thr, thr, 125, 255, THRESH_BINARY ); //Threshold the gray
bitwise_not(thr,thr); //这里先变反转颜色
vector<vector<Point contours; // Vector for storing contours
findContours( thr, contours, RETR_CCOMP, CHAIN_APPROX_SIMPLE ); // Find the contours in the image
for( size_t i = 0; i< contours.size(); i++ ) // iterate through each contour.
{
double area = contourArea( contours[i] ); // Find the area of contour
if( area largest_area )
{
largest_area = area;
largest_contour_index = i; //Store the index of largest contour
bounding_rect = boundingRect( contours[i] ); // Find the bounding rectangle for biggest contour
}
}
drawContours( src, contours,largest_contour_index, Scalar( 0, 255, 0 ), 2 ); // Draw the largest contour using previously stored index.
imshow( "result", src );
waitKey();
return 0;
}
方法二: connectedComponentsWithStats
std::pair< int , int MaxAreaFromSource(Mat srcImage, Mat &dstImage, int index)
{
/*
vector<vector<cv::Point contours; // Vector for storing contours
int largest_area=0;
size_t largest_contour_index=0;
Rect bounding_rect;
findContours( srcImage, contours, RETR_CCOMP, CHAIN_APPROX_SIMPLE ); // Find the contours in the image
for( size_t i = 0; i< contours.size(); i++ ) // iterate through each contour.
{
double area = contourArea( contours[i] ); // Find the area of contour
if( area largest_area )
{
largest_area = area;
largest_contour_index = i; //Store the index of largest contour
bounding_rect = boundingRect( contours[i] ); // Find the bounding rectangle for biggest contour
}
}
Mat dst;
cvtColor(srcImage, dst, CV_GRAY2RGB);
drawContours( dst, contours,largest_contour_index, Scalar( 0, 255, 0 ), 2 ); // Draw the largest contour using previously stored index.
imshow( "result", dst );
waitKey();
printf("%%%%%%%%%%%max area:%d\n", largest_area);
return make_pair( largest_area, index);
*/
cv::Mat img_bool, labels, stats, centroids, img_color, img_gray;
//连通域计算
int nccomps = cv::connectedComponentsWithStats (
srcImage, //二值图像
labels, //和原图一样大的标记图
stats, //nccomps×5的矩阵 表示每个连通区域的外接矩形和面积(pixel)
centroids //nccomps×2的矩阵 表示每个连通区域的质心
);
//cv::imshow("labels", labels);
//cv::waitKey();
vector<cv::Vec3b colors(nccomps);
colors[0] = cv::Vec3b(0,0,0); // background pixels remain black.
printf( "index:%d==================\n",index );
vector< int vec_width,vec_area,vec_height;
for(int label = 1; label < nccomps; ++label)
{
colors[label] = cv::Vec3b( (std::rand()&255), (std::rand()&255), (std::rand()&255) );
std::cout << "Component "<< label << std::endl;
std::cout << "CC_STAT_LEFT = " << stats.at<int (label,cv::CC_STAT_LEFT) << std::endl;
std::cout << "CC_STAT_TOP = " << stats.at<int (label,cv::CC_STAT_TOP) << std::endl;
std::cout << "CC_STAT_WIDTH = " << stats.at<int (label,cv::CC_STAT_WIDTH) << std::endl;
std::cout << "CC_STAT_HEIGHT = " << stats.at<int (label,cv::CC_STAT_HEIGHT) << std::endl;
std::cout << "CC_STAT_AREA = " << stats.at<int (label,cv::CC_STAT_AREA) << std::endl;
std::cout << "CENTER = (" << centroids.at<double (label, 0) <<","<< centroids.at<double (label, 1) << ")"<< std::endl << std::endl;
int area = stats.at<int (label,cv::CC_STAT_AREA);
int left = stats.at<int (label,cv::CC_STAT_LEFT);
int top = stats.at<int (label,cv::CC_STAT_TOP);
int width = stats.at<int (label,cv::CC_STAT_WIDTH);
int height = stats.at<int (label,cv::CC_STAT_HEIGHT);
vec_area.push_back(area);
vec_width.push_back(width);
vec_height.push_back(height);
}
vector<int ::iterator bigwidth = std::max_element(std::begin(vec_width), std::end(vec_width));
vector<int ::iterator bigheight = std::max_element(std::begin(vec_height), std::end(vec_height));
vector<int ::iterator bigarea = std::max_element(std::begin(vec_area), std::end(vec_area));
//printf( "area:%d------------width:%d height:%d \n", *bigarea, *bigwidth, *bigheight );
//按照label值,对不同的连通域进行着色
img_color = cv::Mat::zeros(srcImage.size(), CV_8UC3);
for( int y = 0; y < img_color.rows; y++ )
for( int x = 0; x < img_color.cols; x++ )
{
int label = labels.at<int (y, x);
CV_Assert(0 <= label && label <= nccomps);
img_color.at<cv::Vec3b (y, x) = colors[label];
}
cv::imshow("color", img_color);
cv::waitKey();
return make_pair( *bigarea , index );
}
我先用这个函数实现了一下,效果正确,还是opencv demo 是正确的,网上找了个例子,害死我了。
说明一下:方法一 比 第二种方法 运行速度快很多哦! 这一点很重要。
以上这篇opencv 查找连通区域 最大面积实例就是小编分享给大家的全部内容了,希望能给大家一个参考。