* mln/detection/corner/achard.hh: New. * mln/detection/corner/achard_criterion.hh: New. --- milena/ChangeLog | 7 ++ .../mln/detection/corner/{harris.hh => achard.hh} | 76 +++++--------------- .../{harris_criterion.hh => achard_criterion.hh} | 72 ++++++++++--------- 3 files changed, 63 insertions(+), 92 deletions(-) copy milena/mln/detection/corner/{harris.hh => achard.hh} (58%) copy milena/mln/detection/corner/{harris_criterion.hh => achard_criterion.hh} (58%) diff --git a/milena/ChangeLog b/milena/ChangeLog index b88c960..22afbd2 100644 --- a/milena/ChangeLog +++ b/milena/ChangeLog @@ -1,3 +1,10 @@ +2012-10-05 Jonathan Fabrizio &lt;jonathan(a)lrde.epita.fr&gt; + + Add Achard corner detection. + + * mln/detection/corner/achard.hh: New. + * mln/detection/corner/achard_criterion.hh: New. + 2012-10-04 Jonathan Fabrizio &lt;jonathan(a)lrde.epita.fr&gt; Add test for Harris corner detection. diff --git a/milena/mln/detection/corner/harris.hh b/milena/mln/detection/corner/achard.hh similarity index 58% copy from milena/mln/detection/corner/harris.hh copy to milena/mln/detection/corner/achard.hh index 0acce69..1197ae0 100644 --- a/milena/mln/detection/corner/harris.hh +++ b/milena/mln/detection/corner/achard.hh @@ -23,8 +23,8 @@ // exception does not however invalidate any other reasons why the // executable file might be covered by the GNU General Public License. -#ifndef MLN_DETECTION_CORNER_HARRIS_HH -# define MLN_DETECTION_CORNER_HARRIS_HH +#ifndef MLN_DETECTION_CORNER_ACHARD_HH +# define MLN_DETECTION_CORNER_ACHARD_HH #include <mln/core/site_set/p_array.hh> //#include <mln/win/rectangle2d.hh> @@ -36,11 +36,11 @@ #include <mln/core/alias/w_window2d_int.hh> //#include <mln/core/alias/window2d.hh> -#include <mln/detection/corner/harris_criterion.hh> +#include <mln/detection/corner/achard_criterion.hh> /// \file /// -/// \brief Implementation of Harris corner detection. +/// \brief Implementation of Achard corner detection. namespace mln @@ -50,47 +50,16 @@ namespace mln namespace corner { /** - Computes Harris corner detection on \p in_image + Computes Achard corner detection on \p in_image \param image_in_ The input image - \param k the k parameter in Harris algorithm - \param sigma the standard deviation of the gaussian used in - Harris algorithm \return The list of points detected as corner \author J. Fabrizio */ template<typename I> p_array<mln_site(I)> - harris(const Image<I>& in_image_, float k, float sigma); - - /** - Computes Harris corner detection on \p in_image with the - standard deviation of the guassian sets to 0.34 - - \param image_in_ The input image - \param k the k parameter in Harris algorithm - \return The list of points detected as corner - - \author J. Fabrizio - */ - template<typename I> - p_array<mln_site(I)> - harris(const Image<I>& in_image_, float k); - - /** - Computes Harris corner detection on \p in_image with the k - parameter sets to 0.04 and the standard deviation of the - guassian sets to 0.34. - - \param image_in_ The input image - \return The list of points detected as corner - - \author J. Fabrizio - */ - template<typename I> - p_array<mln_site(I)> - harris(const Image<I>& in_image_); + achard(const Image<I>& in_image_); # ifndef MLN_INCLUDE_ONLY @@ -101,16 +70,16 @@ namespace mln /** \iternal Computes local max to find corner in an image - \param image_in_ The result of harris_criterion + \param image_in_ The result of achard_criterion \return The list of local min \author J. Fabrizio */ template<typename I> p_array<mln_site(I)> - harris_local_max(const Image<I>& in_image_) + achard_local_max(const Image<I>& in_image_) { - trace::exiting("detection::corner::harris_local_max"); + trace::exiting("detection::corner::achard_local_max"); const I& in_image = exact(in_image_); p_array<mln_site(I)> result; mln_piter(I) p(in_image.domain()); @@ -129,7 +98,7 @@ namespace mln result.append(p); } } - trace::exiting("detection::corner::harris_local_max"); + trace::exiting("detection::corner::achard_local_max"); return result; } @@ -137,24 +106,13 @@ namespace mln template<typename I> p_array<mln_site(I)> - harris(const Image<I>& in_image_, float k, float sigma) { - trace::entering("detection::corner::harris"); + achard(const Image<I>& in_image_) { + trace::entering("detection::corner::achard"); mln_ch_convolve(I, w_window2d_int) criterion_image; - criterion_image = harris_criterion(in_image_, k, sigma); - trace::exiting("detection::corner::harris"); - return internal::harris_local_max(criterion_image); - } - - template<typename I> - p_array<mln_site(I)> - harris(const Image<I>& in_image_, float k) { - return harris(in_image_, k, 0.34); - } - - template<typename I> - p_array<mln_site(I)> - harris(const Image<I>& in_image_) { - return harris(in_image_, 0.04, 0.34); + criterion_image = achard_criterion(in_image_); + p_array<mln_site(I)> result = internal::achard_local_max(criterion_image); + trace::exiting("detection::corner::achard"); + return result; } @@ -167,4 +125,4 @@ namespace mln } // end of namespace mln -#endif // ! MLN_DETECTION_CORNER_HARRIS_HH +#endif // ! MLN_DETECTION_CORNER_ACHARD_HH diff --git a/milena/mln/detection/corner/harris_criterion.hh b/milena/mln/detection/corner/achard_criterion.hh similarity index 58% copy from milena/mln/detection/corner/harris_criterion.hh copy to milena/mln/detection/corner/achard_criterion.hh index 0b125c6..b7274a2 100644 --- a/milena/mln/detection/corner/harris_criterion.hh +++ b/milena/mln/detection/corner/achard_criterion.hh @@ -23,8 +23,8 @@ // exception does not however invalidate any other reasons why the // executable file might be covered by the GNU General Public License. -#ifndef MLN_DETECTION_CORNER_HARRIS_CRITERION_HH -# define MLN_DETECTION_CORNER_HARRIS_CRITERION_HH +#ifndef MLN_DETECTION_CORNER_ACHARD_CRITERION_HH +# define MLN_DETECTION_CORNER_ACHARD_CRITERION_HH //#include <mln/io/essential.hh> @@ -35,7 +35,7 @@ /// \file /// -/// \brief Implementation of Harris corner detection. +/// \brief Implementation of Achard, Bigorgne and Devars corner detection. namespace mln @@ -45,39 +45,28 @@ namespace mln namespace corner { /** - Computes Harris corner detection criterion on \p in_image. + Computes Achard, Bigorgne and Devars corner detection criterion on \p in_image. \param image_in_ The input image. - \param k The k parameter in harris algorithm (use 0.04 if you - do not know what to do). - \param sigma The standard deviation of the gaussian used harris algorithm. - \return Harris criterion computed for evey pixel. + \return Achard criterion computed for evey pixel. \author J. Fabrizio */ template<typename I> mln_ch_convolve(I, w_window2d_int) - harris_criterion(const Image<I>& in_image_, float k, float sigma); + achard_criterion(const Image<I>& in_image_); # ifndef MLN_INCLUDE_ONLY - template<typename I> mln_ch_convolve(I, w_window2d_int) - harris_criterion(const Image<I>& in_image_, float k, float sigma) + achard_criterion(const Image<I>& in_image_) { - trace::entering("detection::corner::haris_criterion"); + trace::entering("detection::corner::achard_criterion"); const I& in_image = exact(in_image_); - p_array<mln_site(I)> result; typedef mln_ch_convolve(I, w_window2d_int) O; - O dx_image; - O dy_image; - O dxx_image; - O dxy_image; - O dyy_image; - O harris_criterion(in_image.domain()); typedef dpoint2d D; w_window2d_int dx_grad; @@ -89,27 +78,44 @@ namespace mln .insert(-1, D(-1, 0)) .insert(+1, D(+1, 0)); - dx_image=linear::convolve(in_image, dx_grad); - dy_image=linear::convolve(in_image, dy_grad); + O dx_image=linear::convolve(in_image, dx_grad); + O dy_image=linear::convolve(in_image, dy_grad); + + w_window2d_int mask_M; + mask_M + .insert(+1, D( 0, -1)) + .insert(+1, D( 0, +1)) + .insert(+1, D(+1, -1)) + .insert(+1, D(+1, +1)) + .insert(+1, D(-1, -1)) + .insert(+1, D(-1, +1)) + .insert(+1, D(-1, 0)) + .insert(+1, D(+1, 0)); + + O dxxj_image=linear::convolve(dx_image*dx_image, mask_M); + O dyyj_image=linear::convolve(dy_image*dy_image, mask_M); + O dxyj_image=linear::convolve(dx_image*dy_image, mask_M); - dxx_image=linear::gaussian(dx_image*dx_image, sigma); - dxy_image=linear::gaussian(dx_image*dy_image, sigma); - dyy_image=linear::gaussian(dy_image*dy_image, sigma); + O achard_criterion(in_image.domain()); typedef mln_value(O) V; mln_piter(I) p(in_image.domain()); for_all(p) { - V a = dxx_image(p); - V b = dyy_image(p); - V c = dxy_image(p); - harris_criterion(p)=(a*b-c*c)-k*(a+b)*(a+b); + V ix = dx_image(p); + V iy = dy_image(p); + V ixxj = dxxj_image(p); + V iyyj = dyyj_image(p); + V ixyj = dxyj_image(p); + V grad_magnitude = ix*ix+iy*iy; + achard_criterion(p)=ix*ix*iyyj+iy*iy*ixxj-2*ix*iy*ixyj; + if (grad_magnitude>1) achard_criterion(p)/=grad_magnitude; } - // I output = data::stretch(mln_value(I)(), harris_criterion); - // io::pgm::save(output, "harris-criterion-result.pgm"); + // I output = data::stretch(mln_value(I)(), achard_criterion); + // io::pgm::save(output, "achard-criterion-result.pgm"); - trace::exiting("detection::corner::harris_criterion"); - return harris_criterion; + trace::exiting("detection::corner::achard_criterion"); + return achard_criterion; } # endif // ! MLN_INCLUDE_ONLY @@ -120,4 +126,4 @@ namespace mln } // end of namespace mln -#endif // ! MLN_DETECTION_CORNER_HARRIS_CRITERION_HH +#endif // ! MLN_DETECTION_CORNER_ACHARD_CRITERION_HH -- 1.7.2.5