[Olena-patches] Patch (non) proposal (Convert mln/labelling/ from neighborhoods to windows)

As the time of checking in, I realized this patch might be reverted very soon, since labeling algorithms actually *do* need neighborhoods to express a connexity, not windows (which lack the symmetry property). So, instead of checking in this patch now, I just leave it here (in olena-patches) so that we can possibly use it later, if needed (but I doubt so). ChangeLog: Convert mln/labelling/ from neighborhoods to windows. * mln/canvas/labeling.hh: Use windows instead of neighborhoods. * mln/labeling/blobs.hh, * mln/labeling/flat_zones.hh, * mln/labeling/level.hh, * mln/labeling/foreground.hh, * mln/labeling/regional_minima.hh, * mln/labeling/regional_maxima.hh, * mln/labeling/level.spe.hh, * mln/labeling/background.hh: Convert routine calls using neighborhoods to windows. canvas/labeling.hh | 24 +++++++++++++--------- labeling/background.hh | 18 +++++++---------- labeling/blobs.hh | 46 +++++++++++++++++++ +------------------------ labeling/flat_zones.hh | 40 +++++++++++++++++ +-------------------- labeling/foreground.hh | 18 +++++++---------- labeling/level.hh | 35 ++++++++++++++++++--------------- labeling/level.spe.hh | 42 +++++++++++++++++++ +-------------------- labeling/regional_maxima.hh | 40 +++++++++++++++++ +-------------------- labeling/regional_minima.hh | 40 +++++++++++++++++ +-------------------- 9 files changed, 148 insertions(+), 155 deletions(-) Index: mln/canvas/labeling.hh --- mln/canvas/labeling.hh (revision 1697) +++ mln/canvas/labeling.hh (working copy) @@ -36,7 +36,7 @@ # include <mln/core/concept/image.hh> # include <mln/level/fill.hh> -# include <mln/convert/to_window.hh> // FIXME: to_upper_window +# include <mln/convert/to_upper_window.hh> namespace mln @@ -53,9 +53,13 @@ // Functor. F& f; + // Image type. typedef typename F::I I; - typedef typename F::N N; + // Window type. + typedef typename F::W W; + // Label type. typedef typename F::L L; + // Point set. typedef typename F::S S; // Local type. @@ -100,7 +104,7 @@ F& f; typedef typename F::I I; - typedef typename F::N N; + typedef typename F::W W; typedef typename F::L L; // Auxiliary data. @@ -163,16 +167,16 @@ labeling<F>::pass_1() { mln_fwd_piter(S) p(f.s); - mln_niter(N) n(f.nbh, p); + mln_qiter(W) q(f.win, p); for_all(p) if (f.handles(p)) { make_set(p); - for_all(n) - if (f.input.has(n) && deja_vu(n)) - if (f.equiv(n, p)) - do_union(n, p); + for_all(q) + if (f.input.has(q) && deja_vu(q)) + if (f.equiv(q, p)) + do_union(q, p); else - f.do_no_union(n, p); + f.do_no_union(q, p); deja_vu(p) = true; } } @@ -272,7 +276,7 @@ mln_bkd_pixter(const I) p(f.input); typedef window<mln_dpoint(I)> W; - W win = mln::convert::to_upper_window(f.nbh); + W win = mln::convert::to_upper_window(f.win); mln_qixter(const I, W) n(p, win); for_all(p) if (f.handles(p)) Index: mln/labeling/blobs.hh --- mln/labeling/blobs.hh (revision 1697) +++ mln/labeling/blobs.hh (working copy) @@ -35,7 +35,7 @@ */ # include <mln/core/concept/image.hh> -# include <mln/core/concept/neighborhood.hh> +# include <mln/core/concept/window.hh> # include <mln/level/fill.hh> # include <mln/core/p_queue_fast.hh> @@ -47,16 +47,14 @@ namespace labeling { - /* FIXME: The neighborhood shall not be passed as argument, but - bound to the input image. We can also optionnaly provide a - version of this function for regular-grid-based images where - the neighborhood is replaced by a (user-provided) window. */ + // FIXME: Provide a neighborhood-aware version of these + // algorithms. /*! Connected component labeling of the binary objects of a binary * image. * * \param[in] input The input image. - * \param[in] nbh The neighborhood. + * \param[in] win The connexity of the objects. * \param[out] nlabels The number of labels. * \return The label image. * @@ -65,10 +63,9 @@ * A fast queue is used so that the algorithm is not recursive and * can handle large binary objects (blobs). */ - template <typename I, typename N> + template <typename I, typename W> mln_ch_value(I, unsigned) - blobs(const Image<I>& input, const Neighborhood<N>& nbh, - unsigned& nlabels); + blobs(const Image<I>& input, const Window<W>& win, unsigned& nlabels); # ifndef MLN_INCLUDE_ONLY @@ -79,14 +76,14 @@ namespace generic { - template <typename I, typename N> + template <typename I, typename W> mln_ch_value(I, unsigned) - blobs_(const I& input, const N& nbh, unsigned& nlabels) + blobs_(const I& input, const W& win, unsigned& nlabels) { typedef mln_psite(I) P; P cur; - mln_niter(N) n(nbh, cur); + mln_qiter(W) q(win, cur); p_queue_fast<P> qu; // Initialization. @@ -109,12 +106,12 @@ { cur = qu.front(); qu.pop(); - for_all(n) if (input.has(n)) - if (input(n) && ! output(n)) + for_all(q) if (input.has(q)) + if (input(q) && ! output(q)) { - mln_invariant(! qu.has(n)); - qu.push(n); - output(n) = nlabels; + mln_invariant(! qu.has(q)); + qu.push(q); + output(q) = nlabels; } } while (! qu.is_empty()); @@ -126,12 +123,12 @@ } // end of namespace mln::labeling::impl::generic - template <typename I, typename N> + template <typename I, typename W> mln_ch_value(I, unsigned) - blobs_(const I& input, const N& nbh, unsigned& nlabels) + blobs_(const I& input, const W& win, unsigned& nlabels) { // The only implementation is the generic one. - return generic::blobs_(input, nbh, nlabels); + return generic::blobs_(input, win, nlabels); } } // end of namespace mln::labeling::impl @@ -139,20 +136,19 @@ // Facade. - template <typename I, typename N> + template <typename I, typename W> inline mln_ch_value(I, unsigned) - blobs(const Image<I>& input_, const Neighborhood<N>& nbh_, - unsigned& nlabels) + blobs(const Image<I>& input_, const Window<W>& win_, unsigned& nlabels) { trace::entering("labeling::blobs"); mlc_equal(mln_trait_image_kind(I), mln::trait::image::kind::binary)::check(); const I& input = exact(input_); - const N& nbh = exact(nbh_); + const W& win = exact(win_); mln_precondition(input.has_data()); - mln_ch_value(I, unsigned) output = impl::blobs_(input, nbh, nlabels); + mln_ch_value(I, unsigned) output = impl::blobs_(input, win, nlabels); trace::exiting("labeling::blobs"); return output; Index: mln/labeling/flat_zones.hh --- mln/labeling/flat_zones.hh (revision 1697) +++ mln/labeling/flat_zones.hh (working copy) @@ -34,7 +34,7 @@ */ # include <mln/core/concept/image.hh> -# include <mln/core/concept/neighborhood.hh> +# include <mln/core/concept/window.hh> # include <mln/canvas/labeling.hh> @@ -44,21 +44,19 @@ namespace labeling { - /* FIXME: The neighborhood shall not be passed as argument, but - bound to the input image. We can also optionnaly provide a - version of this function for regular-grid-based images where - the neighborhood is replaced by a (user-provided) window. */ + // FIXME: Provide a neighborhood-aware version of these + // algorithms. /*! Connected component labeling of the flat zones of an image. * * \param[in] input The input image. - * \param[in] nbh The neighborhood to consider. + * \param[in] win The connexity of the flat zones. * \param[out] nlabels The number of labels. * \return The label image. */ - template <typename I, typename N, typename L> + template <typename I, typename W, typename L> mln_ch_value(I, L) - flat_zones(const Image<I>& input, const Neighborhood<N>& nbh, L& nlabels); + flat_zones(const Image<I>& input, const Window<W>& win, L& nlabels); @@ -69,7 +67,7 @@ // Flat zone functor for the labeling canvas. - template <typename I_, typename N_, typename L_> + template <typename I_, typename W_, typename L_> struct flat_zones_functor { typedef mln_psite(I_) P; @@ -77,12 +75,12 @@ // requirements from mln::canvas::labeling: typedef I_ I; - typedef N_ N; + typedef W_ W; typedef L_ L; typedef mln_pset(I) S; const I& input; - const N& nbh; + const W& win; const S& s; bool handles(const P&) const { return true; } @@ -97,9 +95,9 @@ // end of requirements - flat_zones_functor(const I_& input, const N_& nbh) + flat_zones_functor(const I_& input, const W_& win) : input(input), - nbh(nbh), + win(win), s(input.domain()) {} }; @@ -110,14 +108,14 @@ namespace generic { - template <typename I, typename N, typename L> + template <typename I, typename W, typename L> mln_ch_value(I, L) - flat_zones_(const I& input, const N& nbh, L& nlabels) + flat_zones_(const I& input, const W& win, L& nlabels) { trace::entering("labeling::impl::generic::flat_zones_"); - typedef flat_zones_functor<I,N,L> F; - F f(input, nbh); + typedef flat_zones_functor<I,W,L> F; + F f(input, win); canvas::labeling<F> run(f); nlabels = run.nlabels; @@ -134,19 +132,19 @@ // Facade. - template <typename I, typename N, typename L> + template <typename I, typename W, typename L> mln_ch_value(I, L) - flat_zones(const Image<I>& input_, const Neighborhood<N>& nbh_, + flat_zones(const Image<I>& input_, const Window<W>& win_, L& nlabels) { trace::entering("labeling::flat_zones"); const I& input = exact(input_); - const N& nbh = exact(nbh_); + const W& win = exact(win_); mln_precondition(input.has_data()); // Calls the only (generic) impl. mln_ch_value(I, L) output = - impl::generic::flat_zones_(input, nbh, nlabels); + impl::generic::flat_zones_(input, win, nlabels); trace::exiting("labeling::flat_zones"); return output; Index: mln/labeling/level.hh --- mln/labeling/level.hh (revision 1697) +++ mln/labeling/level.hh (working copy) @@ -35,7 +35,7 @@ */ # include <mln/core/concept/image.hh> -# include <mln/core/concept/neighborhood.hh> +# include <mln/core/concept/window.hh> # include <mln/canvas/labeling.hh> # include <mln/level/fill.hh> @@ -50,6 +50,9 @@ namespace labeling { + // FIXME: Provide a neighborhood-aware version of these + // algorithms. + /* FIXME: The neighborhood shall not be passed as argument, but bound to the input image. We can also optionnaly provide a version of this function for regular-grid-based images where @@ -60,14 +63,14 @@ * * \param[in] input The input image. * \param[in] val The level to consider for the labeling. - * \param[in] nbh The neighborhood. + * \param[in] win The connexity of the components. * \param[out] nlabels The number of labels. * \return The label image. */ - template <typename I, typename N, typename L> + template <typename I, typename W, typename L> mln_ch_value(I, L) level(const Image<I>& input, const mln_value(I)& val, - const Neighborhood<N>& nbh, L& nlabels); + const Window<W>& win, L& nlabels); # ifndef MLN_INCLUDE_ONLY @@ -77,7 +80,7 @@ // Generic functor. - template <typename I_, typename N_, typename L_> + template <typename I_, typename W_, typename L_> struct level_functor { typedef mln_psite(I_) P; @@ -85,12 +88,12 @@ // requirements from mln::canvas::labeling: typedef I_ I; - typedef N_ N; + typedef W_ W; typedef L_ L; typedef mln_pset(I) S; const I& input; - const N& nbh; + const W& win; const S& s; bool handles(const P& p) const { return input(p) == val; } @@ -106,9 +109,9 @@ const mln_value(I_)& val; - level_functor(const I_& input, const mln_value(I_)& val, const N_& nbh) + level_functor(const I_& input, const mln_value(I_)& val, const W_& win) : input(input), - nbh(nbh), + win(win), s(input.domain()), val(val) {} @@ -120,15 +123,15 @@ namespace generic { - template <typename I, typename N, typename L> + template <typename I, typename W, typename L> mln_ch_value(I, L) - level_(const I& input, const mln_value(I)& val, const N& nbh, + level_(const I& input, const mln_value(I)& val, const W& win, L& nlabels) { trace::entering("labeling::impl::generic::level_"); - typedef level_functor<I,N,L> F; - F f(input, val, nbh); + typedef level_functor<I,W,L> F; + F f(input, val, win); canvas::labeling<F> run(f); nlabels = run.nlabels; @@ -147,17 +150,17 @@ // Facade. - template <typename I, typename N, typename L> + template <typename I, typename W, typename L> mln_ch_value(I, L) level(const Image<I>& input, const mln_value(I)& val, - const Neighborhood<N>& nbh, L& nlabels) + const Window<W>& win, L& nlabels) { trace::entering("labeling::level"); mln_precondition(exact(input).has_data()); mln_ch_value(I, L) output = impl::level_(mln_trait_image_speed(I)(), - exact(input), val, exact(nbh), nlabels); + exact(input), val, exact(win), nlabels); trace::exiting("labeling::level"); return output; Index: mln/labeling/foreground.hh --- mln/labeling/foreground.hh (revision 1697) +++ mln/labeling/foreground.hh (working copy) @@ -43,16 +43,14 @@ namespace labeling { - /* FIXME: The neighborhood shall not be passed as argument, but - bound to the input image. We can also optionnaly provide a - version of this function for regular-grid-based images where - the neighborhood is replaced by a (user-provided) window. */ + // FIXME: Provide a neighborhood-aware version of these + // algorithms. /*! Connected component labeling of the object part in a binary * image. * * \param[in] input The input image. - * \param[in] nbh The neighborhood to consider. + * \param[in] win The connexity of the foreground. * \param[out] nlabels The number of labels. * \return The label image. * @@ -63,18 +61,18 @@ * * \see mln::labeling::level */ - template <typename I, typename N> + template <typename I, typename W> mln_ch_value(I, unsigned) - foreground(const Image<I>& input, const Neighborhood<N>& nbh, + foreground(const Image<I>& input, const Window<W>& win, unsigned& nlabels); # ifndef MLN_INCLUDE_ONLY - template <typename I, typename N> + template <typename I, typename W> inline mln_ch_value(I, unsigned) - foreground(const Image<I>& input, const Neighborhood<N>& nbh, + foreground(const Image<I>& input, const Window<W>& win, unsigned& nlabels) { trace::entering("labeling::foreground"); @@ -83,7 +81,7 @@ mln_precondition(exact(input).has_data()); mln_ch_value(I, unsigned) output = - labeling::level(input, true, nbh, nlabels); + labeling::level(input, true, win, nlabels); trace::exiting("labeling::foreground"); return output; Index: mln/labeling/regional_minima.hh --- mln/labeling/regional_minima.hh (revision 1697) +++ mln/labeling/regional_minima.hh (working copy) @@ -35,7 +35,7 @@ */ # include <mln/core/concept/image.hh> -# include <mln/core/concept/neighborhood.hh> +# include <mln/core/concept/window.hh> # include <mln/canvas/labeling.hh> # include <mln/level/fill.hh> # include <mln/level/sort_points.hh> @@ -47,23 +47,21 @@ namespace labeling { - /* FIXME: The neighborhood shall not be passed as argument, but - bound to the input image. We can also optionnaly provide a - version of this function for regular-grid-based images where - the neighborhood is replaced by a (user-provided) window. */ + // FIXME: Provide a neighborhood-aware version of these + // algorithms. /*! Connected component labeling of the regional minima of an * image. * * \param[in] input The input image. - * \param[in] nbh The neighborhood to consider. + * \param[in] win The connexity of the minima. * \param[out] nlabels The number of labeled regions. * \return The label image. * */ - template <typename I, typename N, typename L> + template <typename I, typename W, typename L> mln_ch_value(I, L) - regional_minima(const Image<I>& input, const Neighborhood<N>& nbh, + regional_minima(const Image<I>& input, const Window<W>& win, L& nlabels); @@ -74,7 +72,7 @@ // Generic functor. - template <typename I_, typename N_, typename L_> + template <typename I_, typename W_, typename L_> struct regional_minima_functor { typedef mln_psite(I_) P; @@ -82,12 +80,12 @@ // requirements from mln::canvas::labeling: typedef I_ I; - typedef N_ N; + typedef W_ W; typedef L_ L; typedef p_array<P> S; const I& input; - const N& nbh; + const W& win; S s; void init() { level::fill(attr, true); } @@ -106,9 +104,9 @@ mln_ch_value(I, bool) attr; - regional_minima_functor(const I_& input, const N_& nbh) + regional_minima_functor(const I_& input, const W_& win) : input(input), - nbh(nbh), + win(win), s(level::sort_points_increasing(input)), // FIXME: // sort_psites_increasing attr(input.domain()) @@ -122,15 +120,15 @@ namespace generic { - template <typename I, typename N, typename L> + template <typename I, typename W, typename L> mln_ch_value(I, L) - regional_minima_(const I& input, const N& nbh, + regional_minima_(const I& input, const W& win, L& nlabels) { trace::entering("labeling::impl::generic::regional_minima_"); - typedef impl::regional_minima_functor<I,N,L> F; - F f(input, nbh); + typedef impl::regional_minima_functor<I,W,L> F; + F f(input, win); canvas::labeling<F> run(f); nlabels = run.nlabels; @@ -147,19 +145,19 @@ // Facade. - template <typename I, typename N, typename L> + template <typename I, typename W, typename L> mln_ch_value(I, L) - regional_minima(const Image<I>& input_, const Neighborhood<N>& nbh_, + regional_minima(const Image<I>& input_, const Window<W>& win_, L& nlabels) { trace::entering("labeling::regional_minima"); const I& input = exact(input_); - const N& nbh = exact(nbh_); + const W& win = exact(win_); mln_precondition(input.has_data()); // Calls the only (generic) impl. mln_ch_value(I, L) output = - impl::generic::regional_minima_(input, nbh, nlabels); + impl::generic::regional_minima_(input, win, nlabels); trace::exiting("labeling::regional_minima"); return output; Index: mln/labeling/regional_maxima.hh --- mln/labeling/regional_maxima.hh (revision 1697) +++ mln/labeling/regional_maxima.hh (working copy) @@ -35,7 +35,7 @@ */ # include <mln/core/concept/image.hh> -# include <mln/core/concept/neighborhood.hh> +# include <mln/core/concept/window.hh> # include <mln/canvas/labeling.hh> # include <mln/level/fill.hh> # include <mln/level/sort_points.hh> @@ -47,23 +47,21 @@ namespace labeling { - /* FIXME: The neighborhood shall not be passed as argument, but - bound to the input image. We can also optionnaly provide a - version of this function for regular-grid-based images where - the neighborhood is replaced by a (user-provided) window. */ + // FIXME: Provide a neighborhood-aware version of these + // algorithms. /*! Connected component labeling of the regional maxima of an * image. * * \param[in] input The input image. - * \param[in] nbh The neighborhood to consider. + * \param[in] nbh The connexity of the maxima. * \param[out] nlabels The number of labeled regions. * \return The label image. * */ - template <typename I, typename N, typename L> + template <typename I, typename W, typename L> mln_ch_value(I, L) - regional_maxima(const Image<I>& input, const Neighborhood<N>& nbh, + regional_maxima(const Image<I>& input, const Window<W>& win, L& nlabels); @@ -75,7 +73,7 @@ // Generic functor. - template <typename I_, typename N_, typename L_> + template <typename I_, typename W_, typename L_> struct regional_maxima_functor { typedef mln_psite(I_) P; @@ -83,12 +81,12 @@ // requirements from mln::canvas::labeling: typedef I_ I; - typedef N_ N; + typedef W_ W; typedef L_ L; typedef p_array<P> S; const I& input; - const N& nbh; + const W& win; S s; void init() { level::fill(attr, true); } @@ -107,9 +105,9 @@ mln_ch_value(I, bool) attr; - regional_maxima_functor(const I_& input, const N_& nbh) + regional_maxima_functor(const I_& input, const W_& win) : input(input), - nbh(nbh), + win(win), s(level::sort_points_decreasing(input)), // FIXME: // sort_psites_decreasing attr(input.domain()) @@ -123,15 +121,15 @@ namespace generic { - template <typename I, typename N, typename L> + template <typename I, typename W, typename L> mln_ch_value(I, L) - regional_maxima_(const I& input, const N& nbh, + regional_maxima_(const I& input, const W& win, L& nlabels) { trace::entering("labeling::impl::generic::regional_maxima_"); - typedef impl::regional_maxima_functor<I,N,L> F; - F f(input, nbh); + typedef impl::regional_maxima_functor<I,W,L> F; + F f(input, win); canvas::labeling<F> run(f); nlabels = run.nlabels; @@ -148,19 +146,19 @@ // Facade. - template <typename I, typename N, typename L> + template <typename I, typename W, typename L> mln_ch_value(I, L) - regional_maxima(const Image<I>& input_, const Neighborhood<N>& nbh_, + regional_maxima(const Image<I>& input_, const Window<W>& win_, L& nlabels) { trace::entering("labeling::regional_maxima"); const I& input = exact(input_); - const N& nbh = exact(nbh_); + const W& win = exact(win_); mln_precondition(input.has_data()); // Calls the only (generic) impl. mln_ch_value(I, L) output = - impl::generic::regional_maxima_(input, nbh, nlabels); + impl::generic::regional_maxima_(input, win, nlabels); trace::exiting("labeling::regional_maxima"); return output; Index: mln/labeling/level.spe.hh --- mln/labeling/level.spe.hh (revision 1697) +++ mln/labeling/level.spe.hh (working copy) @@ -59,14 +59,14 @@ * * \param[in] input The input image. * \param[in] val The level to consider for the labeling. - * \param[in] nbh The neighborhood. + * \param[in] win The connexity of the components. * \param[out] nlabels The number of labels. * \return The label image. */ - template <typename I, typename N, typename L> + template <typename I, typename W, typename L> mln_ch_value(I, L) level(const Image<I>& input, const mln_value(I)& val, - const Neighborhood<N>& nbh, L& nlabels); + const Window<W>& win, L& nlabels); # ifndef MLN_INCLUDE_ONLY @@ -79,9 +79,9 @@ namespace generic { - template <typename I, typename N, typename L> + template <typename I, typename W, typename L> mln_ch_value(I, L) - level_(const I& input, const mln_value(I)& val, const N& nbh, + level_(const I& input, const mln_value(I)& val, const W& win, L& nlabels); } // end of namespace mln::labeling::impl::generic @@ -90,18 +90,18 @@ // Fastest functor. - template <typename I_, typename N_, typename L_> + template <typename I_, typename W_, typename L_> struct level_fastest_functor { // requirements from mln::canvas::labeling: typedef I_ I; - typedef N_ N; + typedef W_ W; typedef L_ L; typedef mln_pset(I) S; const I& input; - const N& nbh; + const W& win; const S& s; bool handles(unsigned p) const { return input[p] == val; } @@ -118,9 +118,9 @@ const mln_value(I_)& val; level_fastest_functor(const I_& input, const mln_value(I_)& val, - const N_& nbh) + const W_& win) : input(input), - nbh(nbh), + win(win), s(input.domain()), val(val) {} @@ -129,18 +129,18 @@ // Fastest routine. - template <typename I, typename N, typename L> + template <typename I, typename W, typename L> mln_ch_value(I, L) - level_fastest_(const I& input, const mln_value(I)& val, const N& nbh, + level_fastest_(const I& input, const mln_value(I)& val, const W& win, L& nlabels) { trace::entering("labeling::impl::level_fastest_"); - border::adjust(input, nbh.delta()); + border::adjust(input, win.delta()); border::fill(input, value::other(val)); - typedef level_fastest_functor<I,N,L> F; - F f(input, val, nbh); + typedef level_fastest_functor<I,W,L> F; + F f(input, val, win); canvas::labeling_fastest<F> run(f); nlabels = run.nlabels; @@ -153,22 +153,22 @@ // Disjunction between "fastest" and "not fastest". - template <typename I, typename N, typename L> + template <typename I, typename W, typename L> mln_ch_value(I, L) level_(trait::image::speed::any, - const I& input, const mln_value(I)& val, const N& nbh, + const I& input, const mln_value(I)& val, const W& win, L& nlabels) { - return generic::level_(input, val, nbh, nlabels); + return generic::level_(input, val, win, nlabels); } - template <typename I, typename N, typename L> + template <typename I, typename W, typename L> mln_ch_value(I, L) level_(trait::image::speed::fastest, - const I& input, const mln_value(I)& val, const N& nbh, + const I& input, const mln_value(I)& val, const W& win, L& nlabels) { - return level_fastest_(input, val, nbh, nlabels); + return level_fastest_(input, val, win, nlabels); } Index: mln/labeling/background.hh --- mln/labeling/background.hh (revision 1697) +++ mln/labeling/background.hh (working copy) @@ -43,16 +43,14 @@ namespace labeling { - /* FIXME: The neighborhood shall not be passed as argument, but - bound to the input image. We can also optionnaly provide a - version of this function for regular-grid-based images where - the neighborhood is replaced by a (user-provided) window. */ + // FIXME: Provide a neighborhood-aware version of these + // algorithms. /*! Connected component labeling of the background part in a * binary image. * * \param[in] input The input image. - * \param[in] nbh The neighborhood to consider. + * \param[in] win The connexity of the background. * \param[out] nlabels The number of labels. * \return The label image. * @@ -63,18 +61,18 @@ * * \see mln::labeling::level */ - template <typename I, typename N> + template <typename I, typename W> mln_ch_value(I, unsigned) - background(const Image<I>& input, const Neighborhood<N>& nbh, + background(const Image<I>& input, const Window<W>& win, unsigned& nlabels); # ifndef MLN_INCLUDE_ONLY - template <typename I, typename N> + template <typename I, typename W> inline mln_ch_value(I, unsigned) - background(const Image<I>& input, const Neighborhood<N>& nbh, + background(const Image<I>& input, const Window<W>& win, unsigned& nlabels) { trace::entering("labeling::background"); @@ -83,7 +81,7 @@ mln_precondition(exact(input).has_data()); mln_ch_value(I, unsigned) output = - labeling::level(input, false, nbh, nlabels); + labeling::level(input, false, win, nlabels); trace::exiting("labeling::background"); return output;