I would like to detect not regular rectangular objects using OpenCV and approxPolyDP function. In the image I have 4 windows that can be approximate as rectangular contour using the approxPolyDP. But Im not able to detect all of them when set up certain threshold. I filter the windows using the wodth and the height and the angel between the vertices. I would like to have more robust code that can detect all 4 windows. Any help?Here my code
#include "opencv2/highgui/highgui.hpp"
#include "opencv2/imgproc/imgproc.hpp"
#include
#include
#include
using namespace cv;
using namespace std;
Mat src; Mat src_gray;
int thresh = 5;
int max_thresh = 60000;
RNG rng(12345);
void thresh_callback(int, void* );
static double angle(Point pt1, Point pt2, Point pt0)
{
double dx1 = pt1.x - pt0.x;
double dy1 = pt1.y - pt0.y;
double dx2 = pt2.x - pt0.x;
double dy2 = pt2.y - pt0.y;
return (dx1*dx2 + dy1*dy2)/sqrt((dx1*dx1 + dy1*dy1)*(dx2*dx2 + dy2*dy2) + 1e-10);
}
void setLabel(cv::Mat& im, const std::string label, std::vector& contour)
{
int fontface = cv::FONT_HERSHEY_SIMPLEX;
double scale = 0.4;
int thickness = 1;
int baseline = 0;
cv::Size text = cv::getTextSize(label, fontface, scale, thickness, &baseline);
cv::Rect r = cv::boundingRect(contour);
cv::Point pt(r.x + ((r.width - text.width) / 2), r.y + ((r.height + text.height) / 2));
cv::rectangle(im, pt + cv::Point(0, baseline), pt + cv::Point(text.width, -text.height), CV_RGB(255,255,255), CV_FILLED);
cv::putText(im, label, pt, fontface, scale, CV_RGB(0,0,0), thickness, 8);
}
int main()
{
cv::Mat src = cv::imread("p3.png");
resize(src, src, Size(640,480), 0, 0, INTER_CUBIC);
char* source_window = "Source";
namedWindow( source_window, CV_WINDOW_AUTOSIZE );
imshow( source_window, src );
createTrackbar( " Canny thresh:", "Source", &thresh, max_thresh, thresh_callback );
thresh_callback( 0, 0 );
waitKey(0);
return(0);
}
void thresh_callback(int, void* ) {
src = imread("p3.png");
resize(src, src, Size(640,480), 0, 0, INTER_CUBIC);
//================================
Mat gray,bw,dil,erd;
Canny(gray,bw,thresh, thresh*1, 5);
//Canny( src_gray, canny_output, thresh, thresh*1, 3 );
dilate(bw,dil,Mat());
erode(dil,erd,Mat());
Mat tmp=bw.clone();
Size kernalSize (15,20);
Mat element = getStructuringElement (MORPH_RECT, kernalSize, Point(4,4) );
morphologyEx( bw, bw, MORPH_CLOSE, element );
vector> contours;
vector hierarchy;//novo
findContours(bw.clone(), contours, CV_RETR_CCOMP, CV_CHAIN_APPROX_SIMPLE);
vector approx;
Mat dst = src.clone();
for( int i = 0; i< contours.size(); i++ )
{
approxPolyDP(Mat(contours[i]), approx, arcLength(Mat(contours[i]), true) * 0.09, true);
if (approx.size() >= 4.0 && (approx.size() <= 4.1))
{
int vtc = approx.size();
vector cos;
for(int j = 2; j < vtc + 1; j++)
cos.push_back(angle(approx[j%vtc], approx[j-2], approx[j-1]));
sort(cos.begin(), cos.end());
double mincos = cos.front();
double maxcos = cos.back();
if (vtc == 4 && mincos >= -0.6 && maxcos <= 0.6)
{
Rect r = boundingRect(contours[i]);
double ratio = abs(1 - (double)r.width / r.height);
if (r.height >50 && r.width >20 && r.height < 640 && r.width < 640 && r.height>r.width ) /* constraints on region size */
{
//Rect r = boundingRect(contours[i]);
//double ratio = abs(1 - (double)r.width / r.height);
line(dst, approx.at(0), approx.at(1), cvScalar(0,0,255),4);
line(dst, approx.at(1), approx.at(2), cvScalar(0,0,255),4);
line(dst, approx.at(2), approx.at(3), cvScalar(0,0,255),4);
line(dst, approx.at(3), approx.at(0), cvScalar(0,0,255),4);
}
}
}
}
}
Here the source image
Here detected windows
↧