Subversion Repositories OpenCV2-Cookbook

/*------------------------------------------------------------------------------------------*\
   This file contains material supporting chapter 9 of the cookbook:  
   Computer Vision Programming using the OpenCV Library.
   by Robert Laganiere, Packt Publishing, 2011.

   This program is free software; permission is hereby granted to use, copy, modify,
   and distribute this source code, or portions thereof, for any purpose, without fee,
   subject to the restriction that the copyright notice may not be removed
   or altered from any source or altered source distribution.
   The software is released on an as-is basis and without any warranties of any kind.
   In particular, the software is not guaranteed to be fault-tolerant or free from failure.
   The author disclaims all warranties with regard to this software, any use,
   and any consequent failure, is purely the responsibility of the user.
 
   Copyright (C) 2010-2011 Robert Laganiere, www.laganiere.name
\*------------------------------------------------------------------------------------------*/

#include <iostream>
#include <vector>
#include <opencv2/core/core.hpp>
#include <opencv2/imgproc/imgproc.hpp>
#include <opencv2/highgui/highgui.hpp>
#include <opencv2/features2d/features2d.hpp>
#include <opencv2/calib3d/calib3d.hpp>
#include "matcher.h"

int main()
{
        // Read input images
        cv::Mat image1= cv::imread("../parliament1.bmp",0);
        cv::Mat image2= cv::imread("../parliament2.bmp",0);
        if (!image1.data || !image2.data)
                return 0;

    // Display the images
        cv::namedWindow("Image 1");
        cv::imshow("Image 1",image1);
        cv::namedWindow("Image 2");
        cv::imshow("Image 2",image2);

        // Prepare the matcher
        RobustMatcher rmatcher;
        rmatcher.setConfidenceLevel(0.98);
        rmatcher.setMinDistanceToEpipolar(1.0);
        rmatcher.setRatio(0.65f);
        cv::Ptr<cv::FeatureDetector> pfd= new cv::SurfFeatureDetector(10);
        rmatcher.setFeatureDetector(pfd);

        // Match the two images
        std::vector<cv::DMatch> matches;
        std::vector<cv::KeyPoint> keypoints1, keypoints2;
        cv::Mat fundemental= rmatcher.match(image1,image2,matches, keypoints1, keypoints2);

        // draw the matches
        cv::Mat imageMatches;
        cv::drawMatches(image1,keypoints1,  // 1st image and its keypoints
                            image2,keypoints2,  // 2nd image and its keypoints
                                        matches,                        // the matches
                                        imageMatches,           // the image produced
                                        cv::Scalar(255,255,255)); // color of the lines
        cv::namedWindow("Matches");
        cv::imshow("Matches",imageMatches);
       
        // Convert keypoints into Point2f
        std::vector<cv::Point2f> points1, points2;
        for (std::vector<cv::DMatch>::const_iterator it= matches.begin();
                 it!= matches.end(); ++it) {

                         // Get the position of left keypoints
                         float x= keypoints1[it->queryIdx].pt.x;
                         float y= keypoints1[it->queryIdx].pt.y;
                         points1.push_back(cv::Point2f(x,y));
                         // Get the position of right keypoints
                         x= keypoints2[it->trainIdx].pt.x;
                         y= keypoints2[it->trainIdx].pt.y;
                         points2.push_back(cv::Point2f(x,y));
        }

        std::cout << points1.size() << " " << points2.size() << std::endl;

        // Find the homography between image 1 and image 2
        std::vector<uchar> inliers(points1.size(),0);
        cv::Mat homography= cv::findHomography(
                cv::Mat(points1),cv::Mat(points2), // corresponding points
                inliers,        // outputed inliers matches
                CV_RANSAC,      // RANSAC method
                1.);        // max distance to reprojection point

        // Draw the inlier points
        std::vector<cv::Point2f>::const_iterator itPts= points1.begin();
        std::vector<uchar>::const_iterator itIn= inliers.begin();
        while (itPts!=points1.end()) {

                // draw a circle at each inlier location
                if (*itIn)
                        cv::circle(image1,*itPts,3,cv::Scalar(255,255,255),2);
               
                ++itPts;
                ++itIn;
        }

        itPts= points2.begin();
        itIn= inliers.begin();
        while (itPts!=points2.end()) {

                // draw a circle at each inlier location
                if (*itIn)
                        cv::circle(image2,*itPts,3,cv::Scalar(255,255,255),2);
               
                ++itPts;
                ++itIn;
        }

    // Display the images with points
        cv::namedWindow("Image 1 Homography Points");
        cv::imshow("Image 1 Homography Points",image1);
        cv::namedWindow("Image 2 Homography Points");
        cv::imshow("Image 2 Homography Points",image2);

        // Warp image 1 to image 2
        cv::Mat result;
        cv::warpPerspective(image1, // input image
                result,                 // output image
                homography,             // homography
                cv::Size(2*image1.cols,image1.rows)); // size of output image

        // Copy image 1 on the first half of full image
        cv::Mat half(result,cv::Rect(0,0,image2.cols,image2.rows));
        image2.copyTo(half);

    // Display the warp image
        cv::namedWindow("After warping");
        cv::imshow("After warping",result);

        cv::waitKey();
        return 0;
}