Function auto_threshold_image

dlib/image_transforms/thresholding.h:446–550

        typename out_image_type
        >
    void auto_threshold_image (
        const in_image_type& in_img_,
        out_image_type& out_img_
    )
    {
        COMPILE_TIME_ASSERT( pixel_traits<typename image_traits<in_image_type>::pixel_type>::has_alpha == false );
        COMPILE_TIME_ASSERT( pixel_traits<typename image_traits<out_image_type>::pixel_type>::has_alpha == false );
        COMPILE_TIME_ASSERT( pixel_traits<typename image_traits<in_image_type>::pixel_type>::is_unsigned == true );
        COMPILE_TIME_ASSERT( pixel_traits<typename image_traits<out_image_type>::pixel_type>::is_unsigned == true );

        COMPILE_TIME_ASSERT(pixel_traits<typename image_traits<out_image_type>::pixel_type>::grayscale);

        image_view<out_image_type> out_img(out_img_);

        // if there isn't any input image then don't do anything
        if (image_size(in_img_) == 0)
        {
            out_img.clear();
            return;
        }

        unsigned long thresh;
        // find the threshold we should use
        matrix<unsigned long,1> hist;
        get_histogram(in_img_,hist);

        const_image_view<in_image_type> in_img(in_img_);

        // Start our two means (a and b) out at the ends of the histogram
        long a = 0;
        long b = hist.size()-1;
        bool moved_a = true;
        bool moved_b = true;
        while (moved_a || moved_b)
        {
            moved_a = false;
            moved_b = false;

            // catch the degenerate case where the histogram is empty
            if (a >= b)
                break;

            if (hist(a) == 0)
            {
                ++a;
                moved_a = true;
            }

            if (hist(b) == 0)
            {
                --b;
                moved_b = true;
            }
        }
        
        // now do k-means clustering with k = 2 on the histogram. 
        moved_a = true;
        moved_b = true;