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samples/cpp/squares.cpp
A program using pyramid scaling, Canny, contours and contour simplification to find squares in a list of images (pic1-6.png). Returns sequence of squares detected on the image.
// The "Square Detector" program.
// It loads several images sequentially and tries to find squares in
// each image
#include "opencv2/core.hpp"
#include "opencv2/imgproc.hpp"
#include "opencv2/imgcodecs.hpp"
#include "opencv2/highgui.hpp"
#include <iostream>
using namespace cv;
using namespace std;
static void help(const char* programName)
{
cout <<
"\nA program using pyramid scaling, Canny, contours and contour simplification\n"
"to find squares in a list of images (pic1-6.png)\n"
"Returns sequence of squares detected on the image.\n"
"Call:\n"
"./" << programName << " [file_name (optional)]\n"
}
int thresh = 50, N = 11;
const char* wndname = "Square Detection Demo";
// helper function:
// finds a cosine of angle between vectors
// from pt0->pt1 and from pt0->pt2
{
return (dx1*dx2 + dy1*dy2)/sqrt((dx1*dx1 + dy1*dy1)*(dx2*dx2 + dy2*dy2) + 1e-10);
}
// returns sequence of squares detected on the image.
{
squares.clear();
// down-scale and upscale the image to filter out the noise
vector<vector<Point> > contours;
// find squares in every color plane of the image
for( int c = 0; c < 3; c++ )
{
int ch[] = {c, 0};
mixChannels(&timg, 1, &gray0, 1, ch, 1);
// try several threshold levels
for( int l = 0; l < N; l++ )
{
// hack: use Canny instead of zero threshold level.
// Canny helps to catch squares with gradient shading
if( l == 0 )
{
// apply Canny. Take the upper threshold from slider
// and set the lower to 0 (which forces edges merging)
Canny(gray0, gray, 0, thresh, 5);
// dilate canny output to remove potential
// holes between edge segments
}
else
{
// apply threshold if l!=0:
// tgray(x,y) = gray(x,y) < (l+1)*255/N ? 255 : 0
gray = gray0 >= (l+1)*255/N;
}
// find contours and store them all as a list
findContours(gray, contours, RETR_LIST, CHAIN_APPROX_SIMPLE);
vector<Point> approx;
// test each contour
for( size_t i = 0; i < contours.size(); i++ )
{
// approximate contour with accuracy proportional
// to the contour perimeter
// square contours should have 4 vertices after approximation
// relatively large area (to filter out noisy contours)
// and be convex.
// Note: absolute value of an area is used because
// area may be positive or negative - in accordance with the
// contour orientation
if( approx.size() == 4 &&
fabs(contourArea(approx)) > 1000 &&
isContourConvex(approx) )
{
double maxCosine = 0;
for( int j = 2; j < 5; j++ )
{
// find the maximum cosine of the angle between joint edges
double cosine = fabs(angle(approx[j%4], approx[j-2], approx[j-1]));
maxCosine = MAX(maxCosine, cosine);
}
// if cosines of all angles are small
// (all angles are ~90 degree) then write quandrange
// vertices to resultant sequence
if( maxCosine < 0.3 )
squares.push_back(approx);
}
}
}
}
}
int main(int argc, char** argv)
{
const char* names[] = { "pic1.png", "pic2.png", "pic3.png",
"pic4.png", "pic5.png", "pic6.png", 0 };
help(argv[0]);
if( argc > 1)
{
names[0] = argv[1];
names[1] = 0;
}
for( int i = 0; names[i] != 0; i++ )
{
string filename = samples::findFile(names[i]);
{
cout << "Couldn't load " << filename << endl;
continue;
}
vector<vector<Point> > squares;
findSquares(image, squares);
imshow(wndname, image);
int c = waitKey();
if( c == 27 )
break;
}
return 0;
}
int rows
the number of rows and columns or (-1, -1) when the matrix has more than 2 dimensions
Definition: mat.hpp:2137
void mixChannels(const Mat *src, size_t nsrcs, Mat *dst, size_t ndsts, const int *fromTo, size_t npairs)
Copies specified channels from input arrays to the specified channels of output arrays.
void imshow(const String &winname, InputArray mat)
Displays an image in the specified window.
CV_EXPORTS_W Mat imread(const String &filename, int flags=IMREAD_COLOR)
Loads an image from a file.
void polylines(InputOutputArray img, InputArrayOfArrays pts, bool isClosed, const Scalar &color, int thickness=1, int lineType=LINE_8, int shift=0)
Draws several polygonal curves.
void Canny(InputArray image, OutputArray edges, double threshold1, double threshold2, int apertureSize=3, bool L2gradient=false)
Finds edges in an image using the Canny algorithm .
void dilate(InputArray src, OutputArray dst, InputArray kernel, Point anchor=Point(-1,-1), int iterations=1, int borderType=BORDER_CONSTANT, const Scalar &borderValue=morphologyDefaultBorderValue())
Dilates an image by using a specific structuring element.
void pyrUp(InputArray src, OutputArray dst, const Size &dstsize=Size(), int borderType=BORDER_DEFAULT)
Upsamples an image and then blurs it.
void pyrDown(InputArray src, OutputArray dst, const Size &dstsize=Size(), int borderType=BORDER_DEFAULT)
Blurs an image and downsamples it.
void approxPolyDP(InputArray curve, OutputArray approxCurve, double epsilon, bool closed)
Approximates a polygonal curve(s) with the specified precision.
double contourArea(InputArray contour, bool oriented=false)
Calculates a contour area.
double arcLength(InputArray curve, bool closed)
Calculates a contour perimeter or a curve length.
void findContours(InputArray image, OutputArrayOfArrays contours, OutputArray hierarchy, int mode, int method, Point offset=Point())
Finds contours in a binary image.
"black box" representation of the file storage associated with a file on disk.
Definition: core.hpp:106
STL namespace.