FM / image_processing

/usr/include/boost/gil/image_processing/

/usr/include/boost/gil/image_processing

Name	Size	Mode	Actions
filter.hpp	4243	0644	edit dl rm
harris.hpp	3348	0644	edit dl rm
hessian.hpp	2915	0644	edit dl rm
numeric.hpp	10312	0644	edit dl rm
scaling.hpp	4340	0644	edit dl rm
threshold.hpp	16166	0644	edit dl rm

Edit: /usr/include/boost/gil/image_processing/harris.hpp (3348B)

//
// Copyright 2019 Olzhas Zhumabek <anonymous.from.applecity@gmail.com>
//
// Use, modification and distribution are subject to the Boost Software License,
// Version 1.0. (See accompanying file LICENSE_1_0.txt or copy at
// http://www.boost.org/LICENSE_1_0.txt)
//
#ifndef BOOST_GIL_IMAGE_PROCESSING_HARRIS_HPP
#define BOOST_GIL_IMAGE_PROCESSING_HARRIS_HPP

#include <boost/gil/image_view.hpp>
#include <boost/gil/typedefs.hpp>
#include <boost/gil/extension/numeric/kernel.hpp>

namespace boost { namespace gil {
/// \defgroup CornerDetectionAlgorithms
/// \brief Algorithms that are used to find corners in an image
///
/// These algorithms are used to find spots from which
/// sliding the window will produce large intensity change

/// \brief function to record Harris responses
/// \ingroup CornerDetectionAlgorithms
///
/// This algorithm computes Harris responses
/// for structure tensor represented by m11, m12_21, m22 views.
/// Note that m12_21 represents both entries (1, 2) and (2, 1).
/// Window length represents size of a window which is slided around
/// to compute sum of corresponding entries. k is a discrimination
/// constant against edges (usually in range 0.04 to 0.06).
/// harris_response is an out parameter that will contain the Harris responses.
template <typename T, typename Allocator>
void compute_harris_responses(
    boost::gil::gray32f_view_t m11,
    boost::gil::gray32f_view_t m12_21,
    boost::gil::gray32f_view_t m22,
    boost::gil::detail::kernel_2d<T, Allocator> weights,
    float k,
    boost::gil::gray32f_view_t harris_response)
{
    if (m11.dimensions() != m12_21.dimensions() || m12_21.dimensions() != m22.dimensions()) {
        throw std::invalid_argument("m prefixed arguments must represent"
            " tensor from the same image");
    }

auto const window_length = weights.size();
    auto const width = m11.width();
    auto const height = m11.height();
    auto const half_length = window_length / 2;

for (auto y = half_length; y < height - half_length; ++y)
    {
        for (auto x = half_length; x < width - half_length; ++x)
        {
            float ddxx = 0;
            float dxdy = 0;
            float ddyy = 0;
            for (gil::gray32f_view_t::coord_t y_kernel = 0;
                y_kernel < window_length;
                ++y_kernel) {
                for (gil::gray32f_view_t::coord_t x_kernel = 0;
                    x_kernel < window_length;
                    ++x_kernel) {
                    ddxx += m11(x + x_kernel - half_length, y + y_kernel - half_length)
                        .at(std::integral_constant<int, 0>{}) * weights.at(x_kernel, y_kernel);
                    dxdy += m12_21(x + x_kernel - half_length, y + y_kernel - half_length)
                        .at(std::integral_constant<int, 0>{}) * weights.at(x_kernel, y_kernel);
                    ddyy += m22(x + x_kernel - half_length, y + y_kernel - half_length)
                        .at(std::integral_constant<int, 0>{}) * weights.at(x_kernel, y_kernel);
                }
            }
            auto det = (ddxx * ddyy) - dxdy * dxdy;
            auto trace = ddxx + ddyy;
            auto harris_value = det - k * trace * trace;
            harris_response(x, y).at(std::integral_constant<int, 0>{}) = harris_value;
        }
    }
}

}} //namespace boost::gil
#endif

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