/usr/include/gamera/plugins/pagesegmentation.hpp is in python-gamera-dev 3.4.2+svn1437-2.
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*
* Copyright (C) 2007-2009 Stefan Ruloff, Maria Elhachimi,
* Ilya Stoyanov, Robert Butz
* 2010 Tobias Bolten
* 2007-2011 Christoph Dalitz
*
* This program is free software; you can redistribute it and/or
* modify it under the terms of the GNU General Public License
* as published by the Free Software Foundation; either version 2
* of the License, or (at your option) any later version.
*
* This program is distributed in the hope that it will be useful,
* but WITHOUT ANY WARRANTY; without even the implied warranty of
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
* GNU General Public License for more details.
*
* You should have received a copy of the GNU General Public License
* along with this program; if not, write to the Free Software
* Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA.
*/
#ifndef cd20070814_pagesegmentation
#define cd20070814_pagesegmentation
#include <Python.h>
#include <map>
#include <vector>
#include <iostream>
#include <algorithm>
#include <stdexcept>
#include <functional>
#include "gamera.hpp"
#include "gameramodule.hpp"
#include "gamera_limits.hpp"
#include "connected_components.hpp"
#include "plugins/listutilities.hpp"
#include "plugins/projections.hpp"
#include "plugins/segmentation.hpp"
#include "plugins/image_utilities.hpp"
namespace Gamera {
/* Function: median
* Calculates the middle height of the CCs.
* Used for setting defualt parameters in
* runlength_smearing and projection_cutting
*/
int pagesegmentation_median_height(ImageList* ccs) {
vector<int> ccs_heights;
ImageList::iterator i;
if (ccs->empty()) {
throw std::runtime_error("pagesegmentation_median_height: no CC's found in image.");
}
for (i = ccs->begin(); i != ccs->end(); ++i) {
ccs_heights.push_back( (*i)->nrows() );
}
return median(&ccs_heights);
}
/*****************************************************************************
* Run Length Smearing
* IN: Cx - Minimal length of white runs in the rows
* Cy - Minimal length of white runs in the columns
* Csm- Minimal length of white runs row-wise in the almost final image
*
* If you choose "-1" the algorithm will determine the
* median character length in the image to obtain the values for Cx,Cy or
* Csm.
******************************************************************************/
template<class T>
ImageList* runlength_smearing(T &image, int Cx, int Cy, int Csm) {
typedef OneBitImageView view_type;
typedef OneBitImageData data_type;
typedef typename T::value_type value_type;
data_type* img1_data = new data_type(image.size(), image.origin());
view_type* img1 = new view_type(*img1_data);
image_copy_fill(image, *img1);
data_type* img2_data = new data_type(image.size(), image.origin());
view_type* img2 = new view_type(*img2_data);
image_copy_fill(image, *img2);
int Ctemp = 0;
size_t nrows = image.nrows();
size_t ncols = image.ncols();
size_t x, y;
value_type black_val = black(image);
value_type white_val = white(image);
// when no values given, guess them from the Cc size statistics
if (Csm <= 0 || Cy <= 0 || Cx <= 0) {
ImageList* ccs_temp = cc_analysis(image);
int Median = pagesegmentation_median_height(ccs_temp);
for (ImageList::iterator i = ccs_temp->begin(); i != ccs_temp->end(); i++) {
delete *i;
}
delete ccs_temp;
if (Csm <= 0)
Csm = 3 * Median;
if (Cy <= 0)
Cy = 20 * Median;
if (Cx <= 0)
Cx = 20 * Median;
}
// horizontal smearing
for (y = 0; y < nrows; ++y) {
for (x = 0, Ctemp = 0; x < ncols; ++x) {
if (is_white(image.get(Point(x, y)))) {
Ctemp += 1;
} else {
if ((0 != Ctemp) && (Ctemp <= Cx)){
for (int z = 0; z < Ctemp; z++) {
img1->set(Point(x-z-1, y), black_val);
}
}
Ctemp = 0;
}
}
}
// vertical smearing
for (x = 0; x < ncols; ++x) {
for (y = 0, Ctemp = 0; y < nrows; ++y) {
if (is_white(image.get(Point(x, y)))) {
Ctemp += 1;
} else {
if ((0 != Ctemp) && (Ctemp <= Cy)) {
for (int z = 0; z < Ctemp; z++)
img2->set(Point(x, y-z-1), black_val);
}
Ctemp = 0;
}
}
}
// logical AND between both images
for(y = 0; y < nrows; ++y) {
for(x = 0; x < ncols; ++x) {
if ((is_black(img1->get(Point(x, y))))
&& (is_black(img2->get(Point(x, y))))){
img1->set(Point(x, y), black_val);
} else {
img1->set(Point(x, y), white_val);
}
}
}
// again horizontal smearing for removal of small holes
for (y = 0; y < nrows; ++y) {
for (x = 0, Ctemp = 0; x < ncols; ++x) {
if (is_white(img1->get(Point(x, y)))) {
Ctemp += 1;
} else {
if ((0 != Ctemp) && (Ctemp <= Csm)){
for (int z = 0; z < Ctemp; z++)
img1->set(Point(x-z-1, y), black_val);
}
Ctemp = 0;
}
}
}
ImageList* ccs_AND = cc_analysis(*img1);
ImageList* return_ccs = new ImageList();
// create result Cc's
ImageList::iterator i;
for (i = ccs_AND->begin(); i != ccs_AND->end(); ++i) {
Cc* cc = dynamic_cast<Cc*>(*i);
int label = cc->label();
bool containspixel = false; // some segments may not contain black pixels
// Methods "get" and "set" operates relative to the image view
// but the offset of the connected components is not relative
// to the view. (here: (*i)->offset_x() and (*i)->offset_y())
//
// This means that these values must be adjusted for labeling
// the image view.
for (y = 0; y < cc->nrows(); ++y) {
for (x = 0; x < cc->ncols(); ++x) {
if ( is_black(image.get(Point(x+(*i)->offset_x()-image.offset_x(),
y+(*i)->offset_y()-image.offset_y())))
&& is_black(cc->get(Point(x,y))) ) {
image.set(Point(x + cc->offset_x() - image.offset_x(),
y + cc->offset_y() - image.offset_y()), label);
containspixel = true;
}
}
}
// create new CC with the dimensions, offset and label from the
// smeared image, pointing to the original image.
if (containspixel) {
return_ccs->push_back(new ConnectedComponent<data_type>(
*((data_type*)image.data()), // Data
label, // Label
Point((*i)->offset_x(), (*i)->offset_y()), // Point
(*i)->dim()) // Dim
);
}
}
// clean up
for (ImageList::iterator i=ccs_AND->begin(); i!=ccs_AND->end(); i++)
delete *i;
delete ccs_AND;
delete img1->data();
delete img1;
delete img2->data();
delete img2;
return return_ccs;
}
/*-------------------------------------------------------------------------
* Functions for projection_cutting:
* Interne_RXY_Cut(image, Tx, Ty, ccs, noise, label):recursively splits
* the image, sets the label and creates the CCs.
* Start_point(image, ul, lr):search the upper_left point of the sub-image.
* End_point(image,ul,lr):search the lower_right point of the sub-image.
* Split_point:searchs the split point of the image
* rxy_cut(image,Tx,Ty,noise,label):returns the ccs-list
*-------------------------------------------------------------------------*/
/* Function: Start_Point
* This funktion is used to search the first black pixel:
* calculates the coordinates of the begin of the cc
* returns the coordinates of the upper-left point of subimage
*/
template<class T>
Point proj_cut_Start_Point(T& image, Point ul, Point lr) {
Point Start;
for (size_t y = ul.y(); y <= lr.y(); y++) {
for (size_t x = ul.x(); x <= lr.x(); x++) {
if ((image.get(Point(x, y))) != 0) {
Start.x(x);
Start.y(y);
goto endLoop1; // unfortunately there is no break(2) in gorgeous C++
}
}
}
endLoop1:
for (size_t x = ul.x(); x <= lr.x(); x++) {
for (size_t y = ul.y(); y <= lr.y(); y++) {
if ((image.get(Point(x, y))) != 0) {
if (Start.x() > x)
Start.x(x);
goto endLoop2; // unfortunately there is no break(2) in gorgeous C++
}
}
}
endLoop2:
return Start;
}
/* Function: End_Point
* This funktion is used to search the last black pixel:the lower-right point
* of subimage calculates the coordinates of the end of the CC.
*/
template<class T>
Point proj_cut_End_Point(T& image, Point ul, Point lr) {
Point End;
size_t x, y;
for (y = lr.y(); y+1 >= ul.y()+1; y--) {
for (x = lr.x(); x+1 >= ul.x()+1; x--) {
if ((image.get(Point(x, y))) != 0) {
End.x(x);
End.y(y);
goto endLoop1;
}
}
}
endLoop1:
for (x = lr.x(); x+1 > ul.x()+1; x--) {
for (y = lr.y(); y+1 > ul.y()+1; y--) {
if ((image.get(Point(x,y))) != 0){
if (End.x()<x)
End.x(x);
goto endLoop2;
}
}
}
endLoop2:
return End;
}
/* Function: Split_Point
* calculates the coordinates of the split_point.
* The split point is determined
* by finding the largest possible gaps in the X and Y projection of the image.
*/
template<class T>
IntVector * proj_cut_Split_Point(T& image, Point ul, Point lr, int Tx, int Ty, int noise, int gap_treatment, char direction ) {
IntVector * SplitPoints = new IntVector(); //empty IntVector
size_t size;
lr.x()-ul.x()>lr.y()-ul.y()?size=lr.x()-ul.x():size=lr.y()-ul.y();
// probably no need for such big mem-alloc, but necessary in certain situations
int* SplitPoints_Min = new int[size];
int* SplitPoints_Max = new int[size];
int gap_width = 0; // width of the gap
int gap_counter = 0; //number of gaps
if (direction == 'x'){
// Correct Points for Rect() with offset
Point a( ul.x() + image.offset_x(), ul.y() + image.offset_y() );
Point b( lr.x() + image.offset_x(), lr.y() + image.offset_y() );
IntVector *proj_x = projection_rows(image, Rect(a, b));
SplitPoints->push_back(ul.y()); // starting point
for (size_t i = 1; i < proj_x->size(); i++) {
if ((*proj_x)[i] <= noise) {
gap_width++;
if (Ty <= gap_width) {// min-gap <= act-gap?
SplitPoints_Min[gap_counter] = (i + ul.y() - gap_width+1);
SplitPoints_Max[gap_counter] = (i + ul.y()); // finally set to last point of gap
}
}
else {
if (Ty <= gap_width)
gap_counter++;
gap_width = 0;
}
}
delete proj_x;
}
else{ // y-direction
// Correct Points for Rect() with offset
Point a( ul.x() + image.offset_x(), ul.y() + image.offset_y() );
Point b( lr.x() + image.offset_x(), lr.y() + image.offset_y() );
IntVector *proj_y = projection_cols(image, Rect(a, b));
SplitPoints->push_back(ul.x()); // starting point
for (size_t i = 1; i < proj_y->size(); i++) {
if ((*proj_y)[i] <= noise) {
gap_width++;
if (Tx <= gap_width) {// min-gap <= act-gap?
SplitPoints_Min[gap_counter] = (i + ul.x() - gap_width+1);
SplitPoints_Max[gap_counter] = (i + ul.x()); // finally set to last point of gap
}
}
else {
if (Tx <= gap_width)
gap_counter++;
gap_width = 0;
}
}
delete proj_y;
}
for (int i=0; i<gap_counter; i++){
if (0==gap_treatment){ // cut exactly in the middle of the gap -> no unlabeled noise pixels
int mid = (SplitPoints_Min[i] + SplitPoints_Max[i]) / 2;
SplitPoints_Min[i] = mid;
SplitPoints_Max[i] = mid;
}
SplitPoints->push_back(SplitPoints_Min[i]);
SplitPoints->push_back(SplitPoints_Max[i]);
}
direction=='x'? SplitPoints->push_back(lr.y()): SplitPoints->push_back(lr.x()); // ending point
delete [] SplitPoints_Min;
delete [] SplitPoints_Max;
return SplitPoints;
}
/* Function: Interne_RXY_Cut
* This function recursively splits the image in horizontal or
* vertical direction.
* The original image will have all of its pixels "labeled" with a number
* representing each connected component.
*/
template<class T>
void projection_cutting_intern(T& image, Point ul, Point lr, ImageList* ccs,
int Tx, int Ty, int noise, int gap_treatment, char direction, int& label) {
Point Start = proj_cut_Start_Point(image, ul, lr);
Point End = proj_cut_End_Point(image, ul, lr);
IntVector * SplitPoints = proj_cut_Split_Point(image, Start, End, Tx, Ty, noise, gap_treatment, direction);
IntVector::iterator It;
ul.x(Start.x());
ul.y(Start.y());
lr.x(End.x());
lr.y(End.y());
if (!(direction=='y' && SplitPoints->size() == 2)){ // ending condition, SplitPoints==2 => only Start- and Endpoint no gaps
if (direction=='x'){
direction = 'y';
for(It = SplitPoints->begin(); It != SplitPoints->end(); It++){
Point begin, end; // note the lowercase of end, which is not End
begin.x(Start.x());
begin.y(*It);
It++;
end.x(End.x());
end.y(*It);
projection_cutting_intern(image, begin, end, ccs, Tx, Ty, noise, gap_treatment, direction, label);
}
}
else { // direction==y
direction = 'x';
for(It = SplitPoints->begin(); It != SplitPoints->end(); ++It){
Point begin, end; // note the lowercase of end, which is not End
begin.x(*It);
begin.y(Start.y());
It++;
end.x(*It);
end.y(End.y());
projection_cutting_intern(image, begin, end, ccs, Tx, Ty, noise, gap_treatment, direction, label);
}
}
} else {
label++;
for (size_t y = ul.y(); y <= lr.y(); y++) {
for (size_t x = ul.x(); x <= lr.x(); x++) {
if((image.get(Point(x, y))) != 0){
image.set(Point(x, y), label);
}
}
}
Point cc(Start.x() + image.offset_x(), Start.y() + image.offset_y());
ccs->push_back(
new ConnectedComponent<typename T::data_type>(
*((typename T::data_type*)image.data()),
OneBitPixel(label),
cc,
Dim((End.x() - Start.x() + 1), (End.y() - Start.y() + 1))
)
);
}
delete SplitPoints;
}
/*
* Function: rxy_cut
* Returns a list of ccs found in the image.
*/
template<class T>
ImageList* projection_cutting(T& image, int Tx, int Ty, int noise, int gap_treatment) {
int Label = 1;
char direction = 'x';
if (noise < 0) {
noise = 0;
}
// set default values
if (Tx < 1 || Ty < 1) {
ImageList* ccs_temp = cc_analysis(image);
int Median = pagesegmentation_median_height(ccs_temp);
for (ImageList::iterator i = ccs_temp->begin();
i != ccs_temp->end(); i++) {
delete *i;
}
delete ccs_temp;
if (Tx < 1) {
Tx = Median * 7;
}
if (Ty < 1) {
if (Median > 1) Ty = Median / 2;
else Ty = 1;
}
}
// set minimal gap_width
/*if (Tx <= 2){
if (gap_treatment)
Tx=2;
else
Tx=3;
}
if (Ty <= 2){
if (gap_treatment)
Ty=2;
else
Ty=3;
}*/
ImageList* ccs = new ImageList();
Point ul, lr;
ul.x(0);
ul.y(0);
lr.x(image.ncols() - 1);
lr.y(image.nrows() - 1);
projection_cutting_intern(image, ul, lr, ccs, Tx, Ty, noise, gap_treatment, direction, Label);
return ccs;
}
/*
sub_cc_analysis
@param cclist The list of CCs inside the image
@return A tuple with two values
1. the image with the new labels from the new CCs
2. a list of ImageLists
a list-entry is a cc_analysis of a cclist from the argument
*/
template<class T>
PyObject* sub_cc_analysis(T& image, ImageVector &cclist) {
unsigned int pos;
int label = 2; // one is reserved for unlabeled pixels
OneBitImageData *ret_image;
OneBitImageView *ret_view;
OneBitImageData *temp_image;
OneBitImageView *temp_view;
Cc* cc;
ImageVector::iterator iv;
ImageList::iterator il;
typename T::value_type Black = black(image);
ret_image = new OneBitImageData(image.dim(), image.origin());
ret_view = new OneBitImageView(*ret_image, image.origin(), image.dim());
temp_image = new OneBitImageData(image.dim(), image.origin());
temp_view = new OneBitImageView(*temp_image, image.origin(), image.dim());
// Generate a list to store the CCs of all lines
PyObject *return_cclist = PyList_New(cclist.size());
for (iv = cclist.begin(), pos = 0; iv != cclist.end(); iv++, pos++) {
cc = static_cast<Cc*>(iv->first);
// copy the needed CC from the original image(image)
// to the temporary image temp_view
for (size_t y = 0; y < cc->nrows(); y++) {
for (size_t x = 0; x < cc->ncols(); x++) {
if (!is_white(cc->get(Point(x, y)))) {
temp_view->set(Point(x+cc->offset_x()-temp_view->offset_x(), y+cc->offset_y()-temp_view->offset_y()), Black);
}
}
}
// generate a temp image for the cc_analysis,
// it's simply a copy of one cclist entry
OneBitImageView *cc_temp = new OneBitImageView(*temp_image, cc->origin(), cc->dim() );
// Cc_analysis of one list entry
ImageList* ccs_orig = cc_analysis(*cc_temp);
ImageList* return_ccs = new ImageList();
il = ccs_orig->begin();
while (il != ccs_orig->end()) {
cc = static_cast<Cc*>(*il);
return_ccs->push_back(
new ConnectedComponent<typename T::data_type>(
*((typename T::data_type*)ret_view->data()),
OneBitPixel(label),
cc->origin(),
cc->dim()
)
);
// Copy CC over to return image
for (size_t y = 0; y < cc->nrows(); y++) {
for (size_t x = 0; x < cc->ncols(); x++) {
if (!is_white(cc->get(Point(x, y)))) {
ret_view->set(Point(x+cc->offset_x()-ret_view->offset_x(), y+cc->offset_y()-ret_view->offset_y()), label);
}
}
}
// delete the temporary used CCs from the cc_analysis
delete *il;
il++;
label++; // we use consecutive labels in return image
}
// remove copy of Cc in temporary image and clean up
fill_white(*cc_temp);
delete ccs_orig;
delete cc_temp;
// Set the Imagelist into the PyList
// ImageList must be converted to be a valid datatype for the PyList
PyList_SetItem(return_cclist, pos, ImageList_to_python(return_ccs));
delete return_ccs;
}
// delete temporary image
delete temp_view;
delete temp_image;
// Finaly create the return type, a tuple with a image
// and a list of ImageLists
PyObject *return_values = PyTuple_New(2);
PyTuple_SetItem(return_values, 0, create_ImageObject(ret_view));
PyTuple_SetItem(return_values, 1, return_cclist);
return return_values;
}
//
// evaluation of segmentation
//
// for distinguishing Ccs from Gccs and Sccs
class CcLabel {
public:
char image; // 'G' or 'S'
int cclabel;
CcLabel(char i, int c) {image = i; cclabel = c;}
friend int operator<(const CcLabel& c1, const CcLabel& c2) {
if (c1.image == c2.image) return (c1.cclabel < c2.cclabel);
else return c1.image < c2.image;
}
};
// the plugin function
template<class T, class U>
IntVector* segmentation_error(T &Gseg, U &Sseg) {
ImageList* Gccs = ccs_from_labeled_image(Gseg);
ImageList* Sccs = ccs_from_labeled_image(Sseg);
ImageList::iterator ccs_it;
size_t x,y;
int classlabel, Gclasslabel, Sclasslabel;
CcLabel Gcclabel('G',0), Scclabel('S',0), cclabel('A',0);
map<CcLabel,int> classoflabel; // cclabel -> classlabel
multimap<int,CcLabel> labelsofclass; // classlabel -> cclabel
typedef multimap<int,CcLabel>::iterator mm_iterator;
mm_iterator mmit;
pair<mm_iterator,mm_iterator> fromto;
vector<CcLabel> tmplabels;
vector<CcLabel>::iterator vit;
// check for overlaps from Gseg
for (ccs_it = Gccs->begin(), classlabel = 0; ccs_it != Gccs->end(); ++ccs_it, ++classlabel) {
Gclasslabel = classlabel;
Cc* cc = static_cast<Cc*>(*ccs_it);
Gcclabel.cclabel = cc->label();
classoflabel[Gcclabel] = Gclasslabel;
labelsofclass.insert(make_pair(Gclasslabel,Gcclabel));
for (y=0; y < cc->nrows(); y++)
for (x=0; x < cc->ncols(); x++) {
if (!cc->get(Point(x,y))) continue;
Scclabel.cclabel = Sseg.get(Point(cc->ul_x() + x, cc->ul_y() + y));
// in case of overlap:
if (Scclabel.cclabel) {
// check whether segment from S is new
if (classoflabel.find(Scclabel) == classoflabel.end()) {
classoflabel[Scclabel] = Gclasslabel;
labelsofclass.insert(make_pair(Gclasslabel,Scclabel));
} else {
Sclasslabel = classoflabel[Scclabel];
if (Sclasslabel != Gclasslabel) {
// unite both classes, i.e. move Sclasslabel into Gclasslabel
tmplabels.clear();
fromto = labelsofclass.equal_range(Sclasslabel);
for (mmit = fromto.first; mmit != fromto.second; ++mmit) {
cclabel = mmit->second;
classoflabel[cclabel] = Gclasslabel;
tmplabels.push_back(cclabel);
}
labelsofclass.erase(Sclasslabel);
for (vit = tmplabels.begin(); vit != tmplabels.end(); ++vit)
labelsofclass.insert(make_pair(Gclasslabel,*vit));
}
}
}
}
}
// check for CCs from Sseg without overlap (false positives)
for (ccs_it = Sccs->begin(); ccs_it != Sccs->end(); ++ccs_it) {
Cc* cc = static_cast<Cc*>(*ccs_it);
Scclabel.cclabel = cc->label();
if (classoflabel.find(Scclabel) == classoflabel.end()) {
classlabel++;
classoflabel[Scclabel] = classlabel;
labelsofclass.insert(make_pair(classlabel,Scclabel));
}
}
// build up class population numbers and classify error types
int n1,n2,n3,n4,n5,n6,nG,nS;
n1 = n2 = n3 = n4 = n5 = n6 = 0;
for (mmit = labelsofclass.begin(); mmit != labelsofclass.end(); ) {
nG = nS = 0;
fromto = labelsofclass.equal_range(mmit->first);
for (mmit = fromto.first; mmit != fromto.second; ++mmit) {
if (mmit->second.image == 'G') nG++; else nS++;
}
// determine error category
if (nG == 1 && nS == 1) n1++;
else if (nG == 1 && nS == 0) n2++;
else if (nG == 0 && nS == 1) n3++;
else if (nG == 1 && nS > 1) n4++;
else if (nG > 1 && nS == 1) n5++;
else if (nG > 1 && nS > 1) n6++;
else printf("Plugin segment_error: empty equivalence"
" constructed which should not happen\n");
}
// clean up
for (ccs_it = Sccs->begin(); ccs_it != Sccs->end(); ++ccs_it)
delete *ccs_it;
delete Sccs;
for (ccs_it = Gccs->begin(); ccs_it != Gccs->end(); ++ccs_it)
delete *ccs_it;
delete Gccs;
// build return value
IntVector* errors = new IntVector();
errors->push_back(n1); errors->push_back(n2);
errors->push_back(n3); errors->push_back(n4);
errors->push_back(n5); errors->push_back(n6);
return errors;
}
} // end of namespace Gamera
#endif
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