CImg: Image binarization result fails

Question

So, the problem in my following code is that the result of the image binarization becomes too dark. (There was even an example image I have whose binary image becomes wholly black.)

I have been searching any mistake in my code for a very long time, and have found none that seemingly looks problematic to me.

Below is the image I want to binarize:

Image before binarized - in my code is named: "hildebrantmed.bmp"

Below is the resulting binary image:

Image after binarized

Before I show you my source code, here are the 'rules' in the image binarization (since this is an assignment I recently got):

1. I am not allowed to use any other libraries than CImg.
2. The programming language to use is C/C++. Not any other else.
3. Normally, the Otsu's method is the choice. However, I may be allowed to use other algorithms if it is better.

Lastly, here is my source code:

#include <iostream>
#include <CImg.h>

using namespace std;
using namespace cimg_library;

/**
 * Generate histogram of the grayscale image
 */
int * generate_histogram(CImg<unsigned char> img)
{   
    int histogram[256];

    // initialize default values for histogram
    for (int i = 0; i < 256; i++) 
    {
        histogram[i] = 0;
    }

    // increment intensity for histogram
    for (int i = 0; i < img.height(); i++)
    {
        for (int j = 0; j < img.width(); j++)
        {
            int gray_value = img(j, i, 0, 0);
            histogram[gray_value]++;
        }
    }

    return histogram;
}

/**
 * Find threshold value from the grayscale image's histogram
 */
int otsu_threshold(CImg<unsigned char> img)
{
    int * histogram = generate_histogram(img); // image histogram

    int total = img.width() * img.height(); // total pixels

    double sum = 0;

    int i;
    for (i = 0; i < 256; i++)
    {
        sum += i * histogram[i];
    }

    double sumB = 0;
    int wB = 0;
    int wF = 0;

    double var_max = 0;
    int threshold = 0;

    for (i = 0; i < 256; i++)
    {
        wB += histogram[i];
        if (wB == 0) continue;

        wF = total - wB;
        if (wF == 0) continue;

        sumB += (double)(i * histogram[i]);

        double mB = sumB / wB;
        double mF = (sum - sumB) / wF;

        double var_between = (double)wB * (double)wF * (mB - mF) * (mB - mF);

        if (var_between > var_max)
        {
            var_max = var_between;
            threshold = i;
        }
    }

    return threshold;
}

/**
 * Main function
 */
int main(int argc, char * argv[])
{
    // retrieve image from its path
    CImg<unsigned char> img("hildebrantmed.bmp");

    const int width = img.width();
    const int height = img.height();

    // initialize a new image for img's grayscale
    CImg<unsigned char> gray_img(width, height, 1, 1, 0);

    // from RGB divided into three separate channels
    CImg<unsigned char> imgR(width, height, 1, 3, 0);
    CImg<unsigned char> imgG(width, height, 1, 3, 0);
    CImg<unsigned char> imgB(width, height, 1, 3, 0);

    // for all (x, y) pixels in image
    cimg_forXY(img, x, y)
    {
        imgR(x, y, 0, 0) = img(x, y, 0, 0),
        imgG(x, y, 0, 1) = img(x, y, 0, 1),
        imgB(x, y, 0, 2) = img(x, y, 0, 2);

        // separate the channels
        int R = (int)img(x, y, 0, 0);
        int G = (int)img(x, y, 0, 1);
        int B = (int)img(x, y, 0, 2);

        // obtain gray value from different weights of RGB channels
        int gray_value = (int)(0.299 * R + 0.587 * G + 0.114 * B);
        gray_img(x, y, 0, 0) = gray_value;
    }

    // find threshold of grayscale image
    int threshold = otsu_threshold(gray_img);

    // initialize a binary image version of img
    CImg<unsigned char> binary_img(width, height, 1, 1, 0);

    // for every (x, y) pixel in gray_img
    cimg_forXY(img, x, y)
    {
        int gray_value = gray_img(x, y, 0, 0);

        // COMPARE gray_value with threshold
        int binary_value;

        // gray_value > threshold: 255 (white)
        if (gray_value > threshold) binary_value = 255;
        // gray_value < threshold: 0 (black)
        else binary_value = 0;

        // assign binary_value to each of binary_img's pixels
        binary_img(x, y, 0, 0) = binary_value;
    }

    // display the images
    CImgDisplay src_disp(img, "Source image");
    CImgDisplay gray_disp(gray_img, "Grayscale image");
    CImgDisplay binary_disp(binary_img, "Binary image");

    while (!src_disp.is_closed() && !gray_disp.is_closed() && !binary_disp.is_closed())
    {
        src_disp.wait();
        gray_disp.wait();
    }

    return 0;
}

If you find that another algorithm would work better, please provide with the algorithm and source code in your answer. Thanks for your attention.

Answer 1

First error: you're trying to return an array's pointer which actually gets destroyed as soon as the generate_histogram function ends. To make it work properly, you should supply the pointer to an array from the calling function, something like:

{
//[....]
int histogram[256];
generate_histogram(img, histogram);
//[....]
}

int * generate_histogram(CImg<unsigned char> img, int* arHistogram)
{
//[....]
}