[Olena-patches] 4314: Add 2010 code for page segmentation.

https://svn.lrde.epita.fr/svn/oln/trunk/milena/sandbox Index: ChangeLog from Thierry Geraud &lt;thierry.geraud(a)lrde.epita.fr&gt; Add 2010 code for page segmentation. * inim/2010/page: New directory. * inim/2010/page/AUTHORS: New. * inim/2010/page/check_size_functor.hh: New. * inim/2010/page/white.hxx: New. * inim/2010/page/main.cc: New. * inim/2010/page/binarization: New. * inim/2010/page/binarization/binarization.hxx: New. * inim/2010/page/binarization/grayscale.hxx: New. * inim/2010/page/binarization/functors.hh: New. * inim/2010/page/binarization/integral-image.hh: New. * inim/2010/page/binarization/binarization.hh: New. * inim/2010/page/binarization/grayscale.hh: New. * inim/2010/page/binarization/functors.hxx: New. * inim/2010/page/binarization/integral-image.hxx: New. * inim/2010/page/README: New. * inim/2010/page/Makefile: New. * inim/2010/page/white.hh: New. AUTHORS | 3 Makefile | 43 +++++++ README | 51 ++++++++ binarization/binarization.hh | 36 ++++++ binarization/binarization.hxx | 72 ++++++++++++ binarization/functors.hh | 23 +++ binarization/functors.hxx | 33 +++++ binarization/grayscale.hh | 32 +++++ binarization/grayscale.hxx | 15 ++ binarization/integral-image.hh | 34 +++++ binarization/integral-image.hxx | 57 +++++++++ check_size_functor.hh | 30 +++++ main.cc | 89 +++++++++++++++ white.hh | 36 ++++++ white.hxx | 233 ++++++++++++++++++++++++++++++++++++++++ 15 files changed, 787 insertions(+) Index: inim/2010/page/AUTHORS --- inim/2010/page/AUTHORS (revision 0) +++ inim/2010/page/AUTHORS (revision 0) @@ -0,0 +1,3 @@ +hameli_a +denuzi_l +da-mot_s Index: inim/2010/page/check_size_functor.hh --- inim/2010/page/check_size_functor.hh (revision 0) +++ inim/2010/page/check_size_functor.hh (revision 0) @@ -0,0 +1,30 @@ +#ifndef CHECK_SIZE_FUNCTOR_HH_ +# define CHECK_SIZE_FUNCTOR_HH_ + +# include <mln/core/concept/function.hh> + +template <typename P, typename L> +class CheckBoxSize : public mln::Function_v2b< CheckBoxSize<P, L> > +{ +public: + + CheckBoxSize(mln::util::array< mln::box<P> > boxes) + : boxes_ (boxes) + { + } + + bool operator() (L label) const + { + bool condition = + boxes_[label].len(1) >= 200 || + boxes_[label].len(0) >= 200; + return condition; + } + +private: + + mln::util::array< mln::box<P> > boxes_; + +}; + +#endif /* !CHECK_SIZE_FUNCTOR_HH_ */ Index: inim/2010/page/white.hxx --- inim/2010/page/white.hxx (revision 0) +++ inim/2010/page/white.hxx (revision 0) @@ -0,0 +1,233 @@ +#ifndef WHITE_HXX +# define WHITE_HXX + +# include <white.hh> + +namespace whitespace +{ + + template <typename P> + bool is_box_ok (const box<P>& box) + { + return (box.len(0) < 50 && box.len(1) < 30) + && (box.len(0) >= 5 || box.len(1) >= 5); + } + + template <typename I> + util::array< box<mln_psite(I)> > find_connected_components (I& ima) + { +// std::cout << "Computing connected components..." << std::endl; + typedef value::label_16 V; + V num_labels; + mln_ch_value(I, V) labels = labeling::blobs (ima, c8(), num_labels); + +// std::cout << "Computing connected components bounding boxes..." << std::endl; + typedef util::array< box<mln_psite(I)> > A; + A components = + labeling::compute (accu::shape::bbox<mln_psite(I)>(), + labels, num_labels); + +// std::cout << "Writing components image..." << std::endl; + I out (ima.domain()); + mln_fwd_eiter(A) it (components); + A final_components; + for_all (it) + if (is_box_ok (it.element())) + { + final_components.append (it.element()); + data::fill((out | it.element()).rw(), literal::one); + } +// io::pbm::save(out, "out.pbm"); + return final_components; + } + + template <typename P> + bool find_pivot (util::array< box<P> > components, + box<P> bound, + box<P>& pivot) + { + bool found = false; + P bound_min = bound.pmin(); + P bound_max = bound.pmax(); + unsigned int best_dist = 0xffffffff; //bound_max[0] + bound_max[1]; + unsigned int bound_middle_x = (bound_max[0] + bound_min[0]) / 2; + unsigned int bound_middle_y = (bound_max[1] + bound_min[1]) / 2; + + mln_eiter(util::array< box<P> >) it (components); + for_all (it) + { + P it_min = it.element().pmin(); + P it_max = it.element().pmax(); + + if (((bound.pmin()[0] <= it_max[0] && + it_max[0] <= bound.pmax()[0]) || + (bound.pmin()[0] <= it_min[0] && + it_min[0] <= bound.pmax()[0])) && + ((bound.pmin()[1] <= it_max[1] && + it_max[1] <= bound.pmax()[1]) || + (bound.pmin()[1] <= it_min[1] && + it_min[1] <= bound.pmax()[1]))) +// if (inter (it.element(), bound).nsites() != 0) + { + found = true; + unsigned int dist = abs(bound_middle_x - it_min[0]) + + abs(it_max[0] - bound_middle_x) + + abs(bound_middle_y - it_min[1]) + + abs(it_max[1] - bound_middle_y); + if (dist < best_dist) + { + best_dist = dist; + pivot = it.element(); + } + } + } + return found; + } + +// Determinate whether the given box must be considered to search for +// whitespace + template <typename P> + bool searchable_for_whitespace (box<P> pbox, util::array< box<P> > others) + { + if (pbox.nsites() < 4000) + return false; + + if (pbox.len (1) < 2 || pbox.len (0) < 10) + return false; + + typedef util::array< box<P> > A; + mln_fwd_eiter(A) it (others); + + for_all(it) + { + unsigned int box_area = (pbox.pmax()[0] - pbox.pmin()[0]) * + (pbox.pmax()[1] - pbox.pmin()[1]); + + unsigned int left_inter_x = std::max(pbox.pmin()[0], it.element().pmin()[0]); + unsigned int right_inter_x = std::min(pbox.pmax()[0], it.element().pmax()[0]); + unsigned int top_inter_x = std::min(pbox.pmax()[1], it.element().pmax()[1]); + unsigned int bottom_inter_x = std::max(pbox.pmin()[1], it.element().pmin()[1]); + + if ((right_inter_x >= left_inter_x) && (top_inter_x >= bottom_inter_x)) + { + unsigned int inter_area = (right_inter_x - left_inter_x) * + (top_inter_x - bottom_inter_x); + + if (inter_area >= 0.8 * box_area) + return false; + } + } + return true; + } + +// Returns a lower value for high quality rectangles +// For use with a minimal heap + template <typename P> + value::int_u32 quality (box<P> pbox) + { + // Not 0xffffffff because int_u32 constructor + // takes int instead of uint + return (0x7fffffff - pbox.nsites()); + } + + template <typename P> + util::array< box<P> > + find_whitespaces (util::array< box<P> > components, + box<P> bound) + { + typedef util::fibonacci_heap<value::int_u32, box<P> > H; + H h; + util::array< box<P> > res; + h.push (quality(bound), bound); + box<P> b; + box<P> pivot; + while (h.is_valid()) + { + b = h.pop_front(); + if (find_pivot (components, b, pivot)) + { + P pmin = b.pmin(); + P pmax = b.pmax(); + box<P> tmp_box; + for (int i = 0; i < P::dim; ++i) + { + if (pivot.pmax()[i] < b.pmax()[i]) + { + pmin[i] = pivot.pmax()[i] + 1; + tmp_box = box<P>(pmin, pmax); + if (searchable_for_whitespace (tmp_box, res)) + h.push (quality(tmp_box), tmp_box); + pmin[i] = b.pmin()[i]; + } + if (pivot.pmin()[i] > b.pmin()[i]) + { + pmax[i] = pivot.pmin()[i] - 1; + tmp_box = box<P>(pmin, pmax); + if (searchable_for_whitespace (tmp_box, res)) + h.push (quality(tmp_box), tmp_box); + pmax[i] = b.pmax()[i]; + } + } + } + else + // Found a white rectangle \o/ + { + res.append (b); + } + } + return res; + } + + void whitespace_compute (image2d<bool>& ima, + image2d<bool>& cleaned) + { + typedef mln_psite_(image2d<bool>) P; + +// image2d<bool> ima = io::pbm::load (argv[1]); + border::fill (ima, true); + + util::array< box<P> > components = + whitespace::find_connected_components(ima); +// std::cout << "Computing whitespace zones..." << std::endl; + util::array< box<P> > final_components = + whitespace::find_whitespaces (components,ima.domain()); + + +// std::cout << "Merging whitespace zones..." << std::endl; + image2d<bool> zones (ima.domain()); + data::fill (zones, literal::one); + mln_fwd_eiter_(util::array< box<P> >) it (final_components); + for_all (it) + data::fill ((zones | it.element()).rw(), literal::zero); + border::fill (zones, false); + +// std::cout << "Writing whitespace image..." << std::endl; +// io::pbm::save(zones, "zones.pbm"); + +// std::cout << "Cleaning object zones..." << std::endl; + typedef value::label_16 V; + V num_labels; + image2d<V> labels = + labeling::blobs (zones, c8(), num_labels); +// io::pgm::save (labeling::wrap(labels), "labels.pgm"); + + util::array< box<P> > boxes = + labeling::compute (accu::shape::bbox<P>(), labels, num_labels); + + labeling::relabel_inplace (labels, num_labels, + CheckBoxSize<P, V>(boxes)); + labeling::pack_inplace (labels, num_labels); +// io::pgm::save (labeling::wrap(labels), "labels2.pgm"); + + image2d<value::int_u32> size_label = + labeling::compute_image (accu::math::sum<V, value::int_u32>(), + labels, labels, num_labels); + + cleaned = mln::binarization::threshold (size_label, 1); + +// std::cout << "Writing final image..." << std::endl; +// io::pbm::save (cleaned, "white.pbm"); + } +} // End of namespace whitespace + +#endif /* !WHITE_HXX */ Index: inim/2010/page/main.cc --- inim/2010/page/main.cc (revision 0) +++ inim/2010/page/main.cc (revision 0) @@ -0,0 +1,89 @@ +#include <string> +#include <iostream> + +#include <sys/types.h> +#include <sys/stat.h> + +#include <mln/io/ppm/load.hh> +#include <mln/io/pbm/save.hh> +#include <mln/io/pgm/save.hh> +#include <mln/value/int_u8.hh> +#include <mln/core/image/image2d.hh> + +#include <binarization.hh> +#include <grayscale.hh> +#include <white.hh> + +void usage (const std::string& name) +{ + std::cout << "Usage: " << name + << " [-w window_size] [-b] IN.ppm OUT.pbm" << std::endl; + exit (1); +} + +int +main (int argc, + char** argv) +{ + if (argc < 2) + usage(std::string(argv[0])); + + int i = 1; + unsigned int w_val = 51; + bool do_white = true; + + if (std::string(argv[i]) == "-w") + { + if (argc < i + 2) + usage(std::string(argv[0])); + + std::string str_w_val(argv[++i]); + std::istringstream ist(str_w_val); + + ist >> w_val; + ++i; + } + + if (i >= argc) + usage(std::string(argv[0])); + + if (std::string(argv[i]) == "-b") + { + do_white = false; + ++i; + } + + if (i >= argc) + usage(std::string(argv[0])); + + std::string infile(argv[i++]); + + if (i >= argc) + usage(std::string(argv[0])); + + std::string outfile(argv[i]); + + // The original image + mln::image2d<mln::value::rgb8> initial; + mln::io::ppm::load(initial, infile); + const mln::image2d<mln::value::rgb8>& loaded = initial; + + // Grayscale + mln::image2d<mln::value::int_u8> grays(loaded.domain()); + binarization::grayscale(loaded, grays); + + // Binarization + mln::image2d<bool> binarized(loaded.domain()); + binarization::sauvola_threshold(grays, binarized, w_val); + + + if (do_white) + { + // Whitespace + mln::image2d<bool> final(loaded.domain()); + whitespace::whitespace_compute(binarized, final); + mln::io::pbm::save (final, outfile); + } + else + mln::io::pbm::save (binarized, outfile); +} Index: inim/2010/page/binarization/binarization.hxx --- inim/2010/page/binarization/binarization.hxx (revision 0) +++ inim/2010/page/binarization/binarization.hxx (revision 0) @@ -0,0 +1,72 @@ +#ifndef BINARIZATION_HXX +# define BINARIZATION_HXX + +# include <binarization.hh> + +namespace binarization +{ + template<typename T1, typename T2> + void + sauvola_threshold(const image2d<T1>& src, + image2d<T2>& dst, + unsigned int w) + { + // Control the threshold value in the local window + // The higher, the lower the threshold form the local + // mean m(x, y). Badekas et al. said 0.34 was best. + const double k = 0.34; + // Maximum value of the standard deviation (128 for + // grayscale documents). + const double R = 128; + + + // TODO: Merge both calculus into one to improve speed + // Compute the sum of all intensities of src + IntegralImage<T1> simple(src, Identity<T1>()); + // Compute the sum of all squared intensities of src + IntegralImage<T1> squared(src, Square<T1>()); + + int w_2 = w >> 1; + + // Savaula Algorithm with I.I. + for(def::coord row = 0; row < static_cast<def::coord>(dst.nrows()); ++row) + for(def::coord col = 0; col < static_cast<def::coord>(dst.ncols()); ++col) + { + int row_min = std::max(0, row - w_2); + int col_min = std::max(0, col - w_2); + int row_max = std::min(static_cast<int>(dst.nrows() - 1), + row + w_2); + int col_max = std::min(static_cast<int>(dst.ncols() - 1), + col + w_2); + + double wh = (row_max - row_min + 1) * (col_max - col_min + 1); + + // Mean + double m_x_y_tmp = (simple(row_max, col_max) + + simple(row_min, col_min) + - simple(row_max, col_min) + - simple(row_min, col_max)); + + double m_x_y = m_x_y_tmp / wh; + + // Standard deviation + double s_x_y_tmp = (squared(row_max, col_max) + + squared(row_min, col_min) + - squared(row_max, col_min) + - squared(row_min, col_max)); + + double s_x_y = sqrt((s_x_y_tmp - (m_x_y_tmp * m_x_y_tmp) / wh)/(wh-1.0f)); + + // Thresholding + double t_x_y = m_x_y * (1.0 + k * ((s_x_y / R) - 1.0)); + + if (t_x_y > src(point2d(row, col))) + dst(point2d(row, col)) = true; + else + dst(point2d(row, col)) = false; + } + + } +} + +#endif /* !BINARIZATION_HXX */ Index: inim/2010/page/binarization/grayscale.hxx --- inim/2010/page/binarization/grayscale.hxx (revision 0) +++ inim/2010/page/binarization/grayscale.hxx (revision 0) @@ -0,0 +1,15 @@ +#ifndef GRAYSCALE_HXX +# define GRAYSCALE_HXX + +# include <grayscale.hh> + +namespace binarization +{ + void grayscale(const image2d<value::rgb8>& src, + image2d<value::int_u8>& dst) + { + dst = data::transform(src, lum()); + } +} + +#endif /* !GRAYSCALE_HXX */ Index: inim/2010/page/binarization/functors.hh --- inim/2010/page/binarization/functors.hh (revision 0) +++ inim/2010/page/binarization/functors.hh (revision 0) @@ -0,0 +1,23 @@ +#ifndef FUNCTORS_HH +# define FUNCTORS_HH + +namespace binarization +{ + template<typename T> + struct Square + { + Square(); + unsigned long long operator()(T val) const; + }; + + template<typename T> + struct Identity + { + Identity(); + unsigned long long operator()(T val) const; + }; +} + +# include "functors.hxx" + +#endif /* !FUNCTORS_HH */ Index: inim/2010/page/binarization/integral-image.hh --- inim/2010/page/binarization/integral-image.hh (revision 0) +++ inim/2010/page/binarization/integral-image.hh (revision 0) @@ -0,0 +1,34 @@ +#ifndef INTEGRAL_IMAGE_HH +# define INTEGRAL_IMAGE_HH + +# include <mln/core/image/image2d.hh> +# include <mln/value/int_u8.hh> +# include <mln/value/int_u32.hh> +# include <functors.hh> + +namespace binarization +{ + using namespace mln; + + template< typename T > + class IntegralImage + { + public: + template<class F> + IntegralImage(const image2d<T>& i, F func); + ~IntegralImage(); + +// const unsigned long long& operator()(int row, int col) const; + + unsigned long long operator()(int row, int col) const; + + private: + unsigned long long **img_; + int nrows_; + int ncols_; + }; +} + +# include "integral-image.hxx" + +#endif /* !INTEGRAL_IMAGE_HH */ Index: inim/2010/page/binarization/binarization.hh --- inim/2010/page/binarization/binarization.hh (revision 0) +++ inim/2010/page/binarization/binarization.hh (revision 0) @@ -0,0 +1,36 @@ +#ifndef BINARIZATION_HH +# define BINARIZATION_HH + +# include <algorithm> +# include <cmath> + +# include <mln/core/image/image2d.hh> +# include <mln/value/int_u8.hh> +# include <mln/value/int_u32.hh> + +# include <integral-image.hh> +# include <functors.hh> + +namespace binarization +{ + using namespace mln; + + /** + * Sauvola thresholding binarization + * using Integral Images. + * + * \param[in] src The source image + * \param[out] dst The destination image + * \param[in] w Value of the window size + */ + + template<typename T1, typename T2> + void + sauvola_threshold(const image2d<T1>& src, + image2d<T2>& dst, + unsigned int w); +} + +# include <binarization.hxx> + +#endif /* !BINARIZATION_HH */ Index: inim/2010/page/binarization/grayscale.hh --- inim/2010/page/binarization/grayscale.hh (revision 0) +++ inim/2010/page/binarization/grayscale.hh (revision 0) @@ -0,0 +1,32 @@ +#ifndef GRAYSCALE_HH +# define GRAYSCALE_HH + +# include <mln/core/image/image2d.hh> +# include <mln/value/rgb8.hh> +# include <mln/value/int_u8.hh> +# include <mln/data/transform.hh> +# include <mln/literal/colors.hh> + +namespace mln +{ + struct lum : Function_v2v<lum> + { + typedef value::int_u8 result; + result operator()(const value::rgb8& c) const + { + return (c.red() + c.green() + c.blue()) / 3; + } + }; +} + +namespace binarization +{ + using namespace mln; + + void grayscale(const image2d<value::rgb8>& src, + image2d<value::int_u8>& dst); +} + +# include <grayscale.hxx> + +#endif /* !GRAYSCALE_HH */ Index: inim/2010/page/binarization/functors.hxx --- inim/2010/page/binarization/functors.hxx (revision 0) +++ inim/2010/page/binarization/functors.hxx (revision 0) @@ -0,0 +1,33 @@ +#ifndef FUNCTORS_HXX +# define FUNCTORS_HXX + +# include <functors.hxx> + +namespace binarization +{ + template<typename T> + Square<T>::Square() + { } + + template<typename T> + unsigned long long + Square<T>::operator()(T val) const + { + return static_cast<unsigned long long>(val) * static_cast<unsigned long long>(val); + } + + template<typename T> + Identity<T>::Identity() + { } + + template<typename T> + unsigned long long + Identity<T>::operator()(T val) const + { + return static_cast<unsigned long long>(val); + } + + +} + +#endif /* !FUNCTORS_HXX */ Index: inim/2010/page/binarization/integral-image.hxx --- inim/2010/page/binarization/integral-image.hxx (revision 0) +++ inim/2010/page/binarization/integral-image.hxx (revision 0) @@ -0,0 +1,57 @@ +#ifndef INTEGRAL_IMAGE_HXX +# define INTEGRAL_IMAGE_HXX + +# include "integral-image.hh" + +namespace binarization +{ + template<typename T> + template<class F> + IntegralImage<T>::IntegralImage(const image2d<T>& i, F func) + : img_ (NULL), + nrows_ (i.nrows()), + ncols_ (i.ncols()) + { + img_ = static_cast<unsigned long long**>(malloc(sizeof (unsigned long long*) * nrows_)); + for (int n = 0; n < nrows_; ++n) + img_[n] = static_cast<unsigned long long*>(malloc(sizeof (unsigned long long) * ncols_)); + + // FIXME Overflow when super big image? + // unsigned long long not cool for portability + // Look for I.I. in the litterature + img_[0][0] = func(i(point2d(0, 0))); + + for (def::coord row = 1; row < static_cast<def::coord>(i.nrows()); ++row) + img_[row][0] = (*this)(row - 1, 0) + + func(i(point2d(row, 0))); + + for (def::coord col = 1; col < static_cast<def::coord>(i.ncols()); ++col) + img_[0][col] = (*this)(0, col - 1) + + func(i(point2d(0, col))); + + for (def::coord row = 1; row < static_cast<def::coord>(i.nrows()); ++row) + for (def::coord col = 1; col < static_cast<def::coord>(i.ncols()); ++col) + img_[row][col] = (*this)(row - 1, col) + + (*this)(row, col - 1) + - (*this)(row - 1, col - 1) + + func(i(point2d(row, col))); + } + + template< typename T > + IntegralImage<T>::~IntegralImage() + { + for (int n = 0; n < nrows_; ++n) + free(img_[n]); + free(img_); + } + + template< typename T > + unsigned long long + IntegralImage<T>::operator()(int row, + int col) const + { + return img_[row][col]; + } + +} +#endif /* !INTEGRAL_IMAGE_HXX */ Index: inim/2010/page/README --- inim/2010/page/README (revision 0) +++ inim/2010/page/README (revision 0) @@ -0,0 +1,51 @@ +Donc ce que l'on a fait consiste en troix parties: + - Niveaux de gris. + - Binarisation. + - Detection des colonnes de texte. + +- Niveaux de gris: + Pas besoin de trop d'explications ici je pense. + + void binarization::grayscale(const image2d<rgb8>& src, + image2d<int_u8>& dst) + +- Binarisation: + On a effectue une binarisation de Sauvola qui est un algo de seuillage + local (vs global comme Otsu) en se servant d'"Integral Images" pour que + ca trace un peu plus que l'algo de base. Cet Algo retourne une image + de booleens avec en blanc les elements de l'image et en noir le reste. + Il n'a pas de problèmes particulier si ce n'est que si l'image est trop + grosse (vraiment très grosse) avec pleins d'aplat de blanc, on + va dépasser la capacité maximale des unsigned long long utilisés pour les + Integral Images. Un lien vers le papier de référence sur Sauvola: + http://pubs.iupr.org/DATA/2007-IUPR-11Sep_1129.pdf + + La fonction maintenant, avec `w` étant le parametre de taille + de la fenetre utilisée pour les calculs de seuillages locaux: + + void binarization::sauvola_threshold(const image2d<rgb8>& src, + image2d<bool>& dst, + unsigned int w); + + Pour info, Ocropus utilise le même algo sauf que pour déterminer les + parametres optimaux pour une image, ils font plusieurs binarisations + et segmentation jusqu'à ce qu'ils considérent que le résultat soit + bon. + + +- Whitespace: + + On procéde par la recherche des plus grandes zones blanches dans + l'image binarisées. C'est un algo itératif qui cherche à merger + des composantes connexes pour avoir les plus grands aplats de + couleur. Le résultat, c'est que à partir d'une image binarisée, + on va donner une autre image binarisée avec en blanc les colones + et paragraphe de texte et en noir le fond. + + void whitespace::whitespace_compute (image2d<bool>& src, + image2d<bool>& dst); + + +Hésitez pas à nous spammer pour toute forme de questions +la dessus! + Index: inim/2010/page/Makefile --- inim/2010/page/Makefile (revision 0) +++ inim/2010/page/Makefile (revision 0) @@ -0,0 +1,43 @@ +CXX=g++ +INCLUDES=-I. -I./binarization +CXX_FLAGS=-W -Wall -DNDEBUG -O3 -ffast-math +CXXFLAGS = -I. +OBJS= main.o +TARGET=hameli_a +DISTDIR=hameli_a +DISTFILE= Makefile README AUTHORS binarization \ + check_size_functor.hh main.cc \ + white.hh white.hxx + +all: $(TARGET) + +$(TARGET): $(OBJS) + $(CXX) $(DEBUG_FLAGS) $^ -o $@ + +clean: + rm -f *~ *.o + +distclean: clean + rm -rf $(TARGET) + rm -rf *_result + +dist: distclean + rm -rf $(DISTDIR) + mkdir $(DISTDIR) + chmod 755 $(DISTDIR) + cp -r -t $(DISTDIR) $(DISTFILE) + tar czf $(DISTDIR).tar.gz $(DISTDIR) + rm -rf $(DISTDIR) + +distcheck: dist + rm -rf _build + mkdir _build + cp $(DISTDIR).tar.gz _build + cd _build; tar xf $(DISTDIR).tar.gz + cd _build/$(DISTDIR) ; make + +%.o: %.cc + $(CXX) $(CXX_FLAGS) $(CXXFLAGS) $(INCLUDES) $(DEBUG_FLAGS) -c $< + +.PHONY: main.cc +# \ No newline at end of file Index: inim/2010/page/white.hh --- inim/2010/page/white.hh (revision 0) +++ inim/2010/page/white.hh (revision 0) @@ -0,0 +1,36 @@ +#ifndef WHITE_HH +# define WHITE_HH + +#include <cmath> +#include <iostream> +#include <mln/accu/math/sum.hh> +#include <mln/accu/shape/bbox.hh> +#include <mln/binarization/threshold.hh> +#include <mln/core/alias/neighb2d.hh> +#include <mln/core/image/image2d.hh> +#include <mln/data/fill.hh> +#include <mln/labeling/blobs.hh> +#include <mln/labeling/compute.hh> +#include <mln/labeling/compute_image.hh> +#include <mln/labeling/wrap.hh> +#include <mln/util/array.hh> +#include <mln/util/fibonacci_heap.hh> +#include <mln/value/int_u32.hh> +#include <mln/value/label_16.hh> +#include <mln/labeling/relabel.hh> +#include <mln/labeling/pack.hh> +#include <mln/border/fill.hh> +#include <mln/labeling/colorize.hh> +#include <check_size_functor.hh> + +namespace whitespace +{ + using namespace mln; + + void whitespace_compute (image2d<bool>& ima, + image2d<bool>& cleaned); +} + +# include <white.hxx> + +#endif /* !WHITE_HH */