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;

}