Subversion Repositories OpenCV2-Cookbook

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

   This file contains material supporting chapter 4 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>

using namespace std;

#include <opencv2/core/core.hpp>

#include <opencv2/highgui/highgui.hpp>

#include <opencv2/imgproc/imgproc.hpp>

#include <opencv2/video/tracking.hpp>

#include "objectFinder.h"

#include "colorhistogram.h"

int main()

{

        // Read reference image

        cv::Mat image= cv::imread("../baboon1.jpg");

        if (!image.data)

                return 0;

        // Define ROI

        cv::Mat imageROI= image(cv::Rect(110,260,35,40));

        cv::rectangle(image, cv::Rect(110,260,35,40),cv::Scalar(0,0,255));

        // Display image

        cv::namedWindow("Image");

        cv::imshow("Image",image);

        // Get the Hue histogram

        int minSat=65;

        ColorHistogram hc;

        cv::MatND colorhist= hc.getHueHistogram(imageROI);

        ObjectFinder finder;

        finder.setHistogram(colorhist);

        finder.setThreshold(0.2f);

        // Convert to HSV space

        cv::Mat hsv;

        cv::cvtColor(image, hsv, CV_BGR2HSV);

        // Split the image

        vector<cv::Mat> v;

        cv::split(hsv,v);

        // Eliminate pixels with low saturation

        cv::threshold(v[1],v[1],minSat,255,cv::THRESH_BINARY);

        cv::namedWindow("Saturation");

        cv::imshow("Saturation",v[1]);

        // Get back-projection of hue histogram

        int ch[1]={0};

        cv::Mat result= finder.find(hsv,0.0f,180.0f,ch,1);

        cv::namedWindow("Result Hue");

        cv::imshow("Result Hue",result);

        cv::bitwise_and(result,v[1],result);

        cv::namedWindow("Result Hue and");

        cv::imshow("Result Hue and",result);

        // Second image

        image= cv::imread("../baboon3.jpg");

        // Display image

        cv::namedWindow("Image 2");

        cv::imshow("Image 2",image);

        // Convert to HSV space

        cv::cvtColor(image, hsv, CV_BGR2HSV);

        // Split the image

        cv::split(hsv,v);

        // Eliminate pixels with low saturation

        cv::threshold(v[1],v[1],minSat,255,cv::THRESH_BINARY);

        cv::namedWindow("Saturation");

        cv::imshow("Saturation",v[1]);

        // Get back-projection of hue histogram

        result= finder.find(hsv,0.0f,180.0f,ch,1);

        cv::namedWindow("Result Hue");

        cv::imshow("Result Hue",result);

        // Eliminate low stauration pixels

        cv::bitwise_and(result,v[1],result);

        cv::namedWindow("Result Hue and");

        cv::imshow("Result Hue and",result);

        // Get back-projection of hue histogram

        finder.setThreshold(-1.0f);

        result= finder.find(hsv,0.0f,180.0f,ch,1);

        cv::bitwise_and(result,v[1],result);

        cv::namedWindow("Result Hue and raw");

        cv::imshow("Result Hue and raw",result);

        cv::Rect rect(110,260,35,40);

        cv::rectangle(image, rect, cv::Scalar(0,0,255));

        cv::TermCriteria criteria(cv::TermCriteria::MAX_ITER,10,0.01);

        cout << "meanshift= " << cv::meanShift(result,rect,criteria) << endl;

        cv::rectangle(image, rect, cv::Scalar(0,255,0));

        // Display image

        cv::namedWindow("Image 2 result");

        cv::imshow("Image 2 result",image);

        cv::waitKey();

        return 0;

}