opencv square detection radiant floor prob - opencv

Question

working on square detection. the problem is on the radiant floor. as you can see pictures.
any idea for solve this problem ?
thank you.
source image :
output :
source code:
void EdgeDetection::find_squares(const cv::Mat& image,
vector >& squares,cv::Mat& outputFrame) {
unsigned long imageSize = (long) (image.rows * image.cols) / 1000;
if (imageSize > 1200) RESIZE = 9;
else if (imageSize > 600) RESIZE = 5;
else if (imageSize > 300) RESIZE = 3;
else RESIZE = 1;
Mat src(Size(image.cols / RESIZE, image.rows / RESIZE),CV_YUV420sp2BGR);
// Resize src to img size
resize(image, src, src.size() ,0.5, 0.5, INTER_LINEAR);
Mat imgeorj=image;
const int N = 10;//11;
Mat pyr, timg, gray0(src.size(), CV_8U), gray;
// down-scale and upscale the image to filter out the noise
pyrDown(src, pyr, Size(src.cols / 2, src.rows / 2));
pyrUp(pyr, timg, src.size());
#ifdef blured
Mat blurred(src);
medianBlur(src, blurred, 15);
#endif
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);
// Canny(gray0, gray, (10+l), (10+l)*3, 3);
Canny(gray0, gray,50, 200, 3 );
// dilate canny output to remove potential
// holes between edge segments
dilate(gray, gray, Mat(), Point(-1, -1));
//erode(gray, gray, Mat(), Point(-1, -1), 1);
} 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, CV_RETR_LIST, CV_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
approxPolyDP(Mat(contours[i]), approx, arcLength(Mat(contours[i]), true) * 0.02, true);
if (approx.size() == 4 &&
fabs(contourArea(Mat(approx))) > 5000 &&
isContourConvex(Mat(approx))) {
float maxCosine = 0;
for (register int j = 2; j < 5; ++j) {
// find the maximum cosine of the angle between joint edges
float 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);
}
}
}
}
}
debugSquares(squares, imgeorj,outputFrame);
}

Answer 1

You can try using Hough transform for detecting straight edges and use the those for constructing the square.