java - Overlapping shapes recognition (OpenCV) -


i have simple image containing shapes: rectangles , ellipses, in total number of 4 or 5. shapes can rotated, scaled , overlapped. there sample input: sample image task detect of these figures , prepare information them: size, position, rotation, etc. in opinion, core problem fact shapes can overlapped each other. tried search information kind of problem , find opencv library can useful.

opencv has ability detect contours , try fit ellipses or rectangles these contours. problem when shapes overllaped, contours mixed up.

i think following algorithm: detect characteristic points: , put white dot @ them. got these every figure divided separate sections: enter image description here can try link these parts using information, example complexity value (i fit curve approxpolydp contour , read how many parts has). starts hard. other idea try of permutations of linking contours , trying fit figures them. best compilation output.

any ideas how create simple elegant solution?

blurring image helps find intersections seen in code

#include "opencv2/imgproc.hpp" #include "opencv2/highgui.hpp"  using namespace cv;  int main( int argc, char** argv ) {     mat src = imread( argv[1] );     mat gray, blurred;     cvtcolor( src, gray, color_bgr2gray );     threshold( gray, gray, 127, 255, thresh_binary );     gaussianblur( gray, blurred, size(), 9 );     threshold( blurred, blurred, 200, 255, thresh_binary_inv );     gray.setto( 255, blurred );     imshow("result",gray);     waitkey();      return 0; }

result image:enter image description here

step 2

simply, borrowed code generalcontours_demo2.cpp

#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] );     mat gray, blurred;     cvtcolor( src, gray, color_bgr2gray );     threshold( gray, gray, 127, 255, thresh_binary );     gaussianblur( gray, blurred, size(), 5 );     threshold( blurred, blurred, 180, 255, thresh_binary_inv );     gray.setto( 255, blurred );     imshow("result of step 1",gray);      vector<vector<point> > contours;      /// find contours     findcontours( gray.clone(), contours, retr_tree, chain_approx_simple );      /// find rotated rectangles , ellipses each contour     vector<rotatedrect> minrect( contours.size() );     vector<rotatedrect> minellipse( contours.size() );      for( size_t = 0; < contours.size(); i++ )     {         minrect[i] = minarearect( mat(contours[i]) );         if( contours[i].size() > 5 )         {             minellipse[i] = fitellipse( mat(contours[i]) );         }     }      /// draw contours + rotated rects + ellipses     for( size_t = 0; i< contours.size(); i++ )     {         mat drawing = src.clone();         // contour         //drawcontours( drawing, contours, (int)i, color, 1, 8, vector<vec4i>(), 0, point() );         // ellipse         ellipse( drawing, minellipse[i], scalar( 0, 0, 255 ), 2 );         // rotated rectangle         point2f rect_points[4];         minrect[i].points( rect_points );         for( int j = 0; j < 4; j++ )             line( drawing, rect_points[j], rect_points[(j+1)%4], scalar( 0, 255, 0 ), 2 );         /// show in window         imshow( "results of step 2", drawing );         waitkey();     }      return 0; }

you can following result images among others. hope solve final step. enter image description here enter image description here enter image description here enter image description here


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