Hi.
Another way could be to find the contours by thresholding your image (if all your images look binary) and finding the bounding rectangle for each contour.
In C++, using the tutorial: Creating Bounding boxes and circles for contours
#include <iostream>
#include <opencv2/highgui/highgui.hpp>
#include <opencv2/imgproc/imgproc.hpp>
using namespace cv;
using namespace std;
//See http://docs.opencv.org/doc/tutorials/imgproc/shapedescriptors/bounding_rects_circles/bounding_rects_circles.html
int main( int argc, char** argv )
{
Mat img = imread("crop_rectangle.png", CV_LOAD_IMAGE_GRAYSCALE);
Mat threshold_output;
/// Detect edges using Threshold
threshold( img, threshold_output, 20, 255, THRESH_BINARY );
imshow( "threshold_output", threshold_output );
vector<vector<Point> > contours;
vector<Vec4i> hierarchy;
/// Find contours
findContours( threshold_output, contours, hierarchy, CV_RETR_TREE, CV_CHAIN_APPROX_SIMPLE, Point(0, 0) );
/// Approximate contours to polygons + get bounding rects
vector<vector<Point> > contours_poly( contours.size() );
Rect boundRect;
double maxArea = 0.0;
for( int i = 0; i < contours.size(); i++ )
{
double area = contourArea(contours[i]);
if(area > maxArea) {
maxArea = area;
approxPolyDP( Mat(contours[i]), contours_poly[i], 3, true );
boundRect = boundingRect( Mat(contours_poly[i]) );
}
}
Mat cropImage = img(boundRect);
imshow("cropImage", cropImage);
waitKey(0);
return(0);
}
Hi, may be you can use houghline to detect line and to find 4 coners position.
can you tell me how to use houghline to find the 4 corners? do you have a java example?