opencv 查找連通區(qū)域 最大面積實例
今天在弄一個查找連通的最大面積的問題。
要把圖像弄成黑底,白字,這樣才可以正確找到。
然后調(diào)用下邊的方法:
RETR_CCOMP:提取所有輪廓,并將輪廓組織成雙層結(jié)構(gòu)(two-level hierarchy),頂層為連通域的外圍邊界,次層位內(nèi)層邊界
#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); //這里先變反轉(zhuǎn)顏色
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;
//連通域計算
int nccomps = cv::connectedComponentsWithStats (
srcImage, //二值圖像
labels, //和原圖一樣大的標記圖
stats, //nccomps×5的矩陣 表示每個連通區(qū)域的外接矩形和面積(pixel)
centroids //nccomps×2的矩陣 表示每個連通區(qū)域的質(zhì)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,對不同的連通域進行著色
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 );
}
我先用這個函數(shù)實現(xiàn)了一下,效果正確,還是opencv demo 是正確的,網(wǎng)上找了個例子,害死我了。
說明一下:方法一 比 第二種方法 運行速度快很多哦! 這一點很重要。
以上這篇opencv 查找連通區(qū)域 最大面積實例就是小編分享給大家的全部內(nèi)容了,希望能給大家一個參考,也希望大家多多支持腳本之家。
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