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>

using namespace std;

#include "cv.h"

#include "highgui.h"

#include "histogram.h"

int main()

{

        // Read input image

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

        if (!image.data)

                return 0;

    // Display the image

        cv::namedWindow("Image");

        cv::imshow("Image",image);

        // The histogram object

        Histogram1D h;

    // Compute the histogram

        cv::MatND histo= h.getHistogram(image);

        // Loop over each bin

        for (int i=0; i<256; i++)

                cout << "Value " << i << " = " << histo.at<float>(i) << endl;  

        // Display a histogram as an image

        cv::namedWindow("Histogram");

        cv::imshow("Histogram",h.getHistogramImage(image));

        // creating a binary image by thresholding at the valley

        cv::Mat thresholded;

        cv::threshold(image,thresholded,60,255,cv::THRESH_BINARY);

        // Display the thresholded image

        cv::namedWindow("Binary Image");

        cv::imshow("Binary Image",thresholded);

        cv::imwrite("binary.bmp",thresholded);

        // Equalize the image

        cv::Mat eq= h.equalize(image);

        // Show the result

        cv::namedWindow("Equalized Image");

        cv::imshow("Equalized Image",eq);

        // Show the new histogram

        cv::namedWindow("Equalized Histogram");

        cv::imshow("Equalized Histogram",h.getHistogramImage(eq));

        // Stretch the image ignoring bins with less than 5 pixels

        cv::Mat str= h.stretch(image,5);

        // Show the result

        cv::namedWindow("Stretched Image");

        cv::imshow("Stretched Image",str);

        // Show the new histogram

        cv::namedWindow("Stretched Histogram");

        cv::imshow("Stretched Histogram",h.getHistogramImage(str));

        // Create an image inversion table

        uchar lookup[256];

        for (int i=0; i<256; i++) {

                lookup[i]= 255-i;

        }

        // Apply lookup and display negative image

        cv::namedWindow("Negative image");

        cv::imshow("Negative image",h.applyLookUp(image,lookup));

        cv::waitKey();

        return 0;

}