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 #include 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> 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> 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();

vectorcolors(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(label,cv::CC_STAT_LEFT) << std::endl;

std::cout << "CC_STAT_TOP = " << stats.at(label,cv::CC_STAT_TOP) << std::endl;

std::cout << "CC_STAT_WIDTH = " << stats.at(label,cv::CC_STAT_WIDTH) << std::endl;

std::cout << "CC_STAT_HEIGHT = " << stats.at(label,cv::CC_STAT_HEIGHT) << std::endl;

std::cout << "CC_STAT_AREA = " << stats.at(label,cv::CC_STAT_AREA) << std::endl;

std::cout << "CENTER = (" << centroids.at(label, 0)

int area = stats.at(label,cv::CC_STAT_AREA);

int left = stats.at(label,cv::CC_STAT_LEFT);

int top = stats.at(label,cv::CC_STAT_TOP);

int width = stats.at(label,cv::CC_STAT_WIDTH);

int height = stats.at(label,cv::CC_STAT_HEIGHT);

vec_area.push_back(area);

vec_width.push_back(width);

vec_height.push_back(height);

}

vector::iterator bigwidth = std::max_element(std::begin(vec_width), std::end(vec_width));

vector::iterator bigheight = std::max_element(std::begin(vec_height), std::end(vec_height));

vector::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(y, x);

CV_Assert(0 <= label && label <= nccomps);

img_color.at(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。