Subversion Repositories OpenCV2-Cookbook

/*------------------------------------------------------------------------------------------*\

   This file contains material supporting chapter 8 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 "harrisDetector.h"

int main()

{

        // Read input image

        cv::Mat image= cv::imread("../church01.jpg",0);

        if (!image.data)

                return 0;

    // Display the image

        cv::namedWindow("Original Image");

        cv::imshow("Original Image",image);

        // Detect Harris Corners

        cv::Mat cornerStrength;

        cv::cornerHarris(image,cornerStrength,

                          3,     // neighborhood size

                                         3,     // aperture size

                                         0.01); // Harris parameter

   // threshold the corner strengths

        cv::Mat harrisCorners;

        double threshold= 0.0001;

        cv::threshold(cornerStrength,harrisCorners,

                 threshold,255,cv::THRESH_BINARY_INV);

    // Display the corners

        cv::namedWindow("Harris Corner Map");

        cv::imshow("Harris Corner Map",harrisCorners);

        // Create Harris detector instance

        HarrisDetector harris;

    // Compute Harris values

        harris.detect(image);

    // Detect Harris corners

        std::vector<cv::Point> pts;

        harris.getCorners(pts,0.01);

        // Draw Harris corners

        harris.drawOnImage(image,pts);

    // Display the corners

        cv::namedWindow("Harris Corners");

        cv::imshow("Harris Corners",image);

        // Read input image

        image= cv::imread("../church01.jpg",0);

        // Compute good features to track

        std::vector<cv::Point2f> corners;

        cv::goodFeaturesToTrack(image,corners,

                500,    // maximum number of corners to be returned

                0.01,   // quality level

                10);    // minimum allowed distance between points

        // for all corners

        std::vector<cv::Point2f>::const_iterator it= corners.begin();

        while (it!=corners.end()) {

                // draw a circle at each corner location

                cv::circle(image,*it,3,cv::Scalar(255,255,255),2);

                ++it;

        }

    // Display the corners

        cv::namedWindow("Good Features to Track");

        cv::imshow("Good Features to Track",image);

        // Read input image

        image= cv::imread("../church01.jpg",0);

        // vector of keypoints

        std::vector<cv::KeyPoint> keypoints;

        // Construction of the Good Feature to Track detector 

        cv::GoodFeaturesToTrackDetector gftt(

                500,    // maximum number of corners to be returned

                0.01,   // quality level

                10);    // minimum allowed distance between points

        // point detection using FeatureDetector method

        gftt.detect(image,keypoints);

        cv::drawKeypoints(image,                // original image

                keypoints,                                      // vector of keypoints

                image,                                          // the resulting image

                cv::Scalar(255,255,255),        // color of the points

                cv::DrawMatchesFlags::DRAW_OVER_OUTIMG); //drawing flag

    // Display the corners

        cv::namedWindow("Good Features to Track Detector");

        cv::imshow("Good Features to Track Detector",image);

        // Read input image

        image= cv::imread("../church01.jpg",0);

        keypoints.clear();

        cv::FastFeatureDetector fast(40);

        fast.detect(image,keypoints);

        cv::drawKeypoints(image,keypoints,image,cv::Scalar(255,255,255),cv::DrawMatchesFlags::DRAW_OVER_OUTIMG);

    // Display the corners

        cv::namedWindow("FAST Features");

        cv::imshow("FAST Features",image);

        // Read input image

        image= cv::imread("../church03.jpg",0);

        keypoints.clear();

        // Construct the SURF feature detector object

        cv::SurfFeatureDetector surf(2500);

        // Detect the SURF features

        surf.detect(image,keypoints);

        cv::Mat featureImage;

        cv::drawKeypoints(image,keypoints,featureImage,cv::Scalar(255,255,255),cv::DrawMatchesFlags::DRAW_RICH_KEYPOINTS);

    // Display the corners

        cv::namedWindow("SURF Features");

        cv::imshow("SURF Features",featureImage);

        // Read input image

        image= cv::imread("../church01.jpg",0);

        keypoints.clear();

        // Construct the SURF feature detector object

        cv::SiftFeatureDetector sift(

                0.03,  // feature threshold

                10.);  // threshold to reduce

                   // sensitivity to lines

        // Detect the SURF features

        sift.detect(image,keypoints);

        cv::drawKeypoints(image,keypoints,featureImage,cv::Scalar(255,255,255),cv::DrawMatchesFlags::DRAW_RICH_KEYPOINTS);

    // Display the corners

        cv::namedWindow("SIFT Features");

        cv::imshow("SIFT Features",featureImage);

        // Read input image

        image= cv::imread("../church01.jpg",0);

        keypoints.clear();

        cv::MserFeatureDetector mser;

        mser.detect(image,keypoints);

        // Draw the keypoints with scale and orientation information

        cv::drawKeypoints(image,                // original image

                keypoints,                                      // vector of keypoints

                featureImage,                           // the resulting image

                cv::Scalar(255,255,255),        // color of the points

                cv::DrawMatchesFlags::DRAW_RICH_KEYPOINTS); //drawing flag

    // Display the corners

        cv::namedWindow("MSER Features");

        cv::imshow("MSER Features",featureImage);

        cv::waitKey();

        return 0;

}