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tesseract/textord/wordseg.cpp

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/**********************************************************************
* File: wordseg.cpp (Formerly wspace.c)
* Description: Code to segment the blobs into words.
* Author: Ray Smith
* Created: Fri Oct 16 11:32:28 BST 1992
*
* (C) Copyright 1992, Hewlett-Packard Ltd.
** Licensed under the Apache License, Version 2.0 (the "License");
** you may not use this file except in compliance with the License.
** You may obtain a copy of the License at
** http://www.apache.org/licenses/LICENSE-2.0
** Unless required by applicable law or agreed to in writing, software
** distributed under the License is distributed on an "AS IS" BASIS,
** WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
** See the License for the specific language governing permissions and
** limitations under the License.
*
**********************************************************************/
#ifdef __UNIX__
#include <assert.h>
#endif
#include "stderr.h"
#include "blobbox.h"
#include "statistc.h"
#include "drawtord.h"
#include "makerow.h"
#include "pitsync1.h"
#include "tovars.h"
#include "topitch.h"
#include "cjkpitch.h"
#include "textord.h"
#include "fpchop.h"
#include "wordseg.h"
// Include automatically generated configuration file if running autoconf.
#ifdef HAVE_CONFIG_H
#include "config_auto.h"
#endif
#define EXTERN
EXTERN BOOL_VAR(textord_fp_chopping, TRUE, "Do fixed pitch chopping");
EXTERN BOOL_VAR(textord_force_make_prop_words, FALSE,
"Force proportional word segmentation on all rows");
EXTERN BOOL_VAR(textord_chopper_test, FALSE,
"Chopper is being tested.");
#define FIXED_WIDTH_MULTIPLE 5
#define BLOCK_STATS_CLUSTERS 10
/**
* @name make_single_word
*
* For each row, arrange the blobs into one word. There is no fixed
* pitch detection.
*/
void make_single_word(bool one_blob, TO_ROW_LIST *rows, ROW_LIST* real_rows) {
TO_ROW_IT to_row_it(rows);
ROW_IT row_it(real_rows);
for (to_row_it.mark_cycle_pt(); !to_row_it.cycled_list();
to_row_it.forward()) {
TO_ROW* row = to_row_it.data();
// The blobs have to come out of the BLOBNBOX into the C_BLOB_LIST ready
// to create the word.
C_BLOB_LIST cblobs;
C_BLOB_IT cblob_it(&cblobs);
BLOBNBOX_IT box_it(row->blob_list());
for (;!box_it.empty(); box_it.forward()) {
BLOBNBOX* bblob= box_it.extract();
if (bblob->joined_to_prev() || (one_blob && !cblob_it.empty())) {
if (bblob->cblob() != NULL) {
C_OUTLINE_IT cout_it(cblob_it.data()->out_list());
cout_it.move_to_last();
cout_it.add_list_after(bblob->cblob()->out_list());
delete bblob->cblob();
}
} else {
if (bblob->cblob() != NULL)
cblob_it.add_after_then_move(bblob->cblob());
}
delete bblob;
}
// Convert the TO_ROW to a ROW.
ROW* real_row = new ROW(row, static_cast<inT16>(row->kern_size),
static_cast<inT16>(row->space_size));
WERD_IT word_it(real_row->word_list());
WERD* word = new WERD(&cblobs, 0, NULL);
word->set_flag(W_BOL, TRUE);
word->set_flag(W_EOL, TRUE);
word->set_flag(W_DONT_CHOP, one_blob);
word_it.add_after_then_move(word);
row_it.add_after_then_move(real_row);
}
}
/**
* make_words
*
* Arrange the blobs into words.
*/
void make_words(tesseract::Textord *textord,
ICOORD page_tr, // top right
float gradient, // page skew
BLOCK_LIST *blocks, // block list
TO_BLOCK_LIST *port_blocks) { // output list
TO_BLOCK_IT block_it; // iterator
TO_BLOCK *block; // current block
if (textord->use_cjk_fp_model()) {
compute_fixed_pitch_cjk(page_tr, port_blocks);
} else {
compute_fixed_pitch(page_tr, port_blocks, gradient, FCOORD(0.0f, -1.0f),
!(BOOL8) textord_test_landscape);
}
textord->to_spacing(page_tr, port_blocks);
block_it.set_to_list(port_blocks);
for (block_it.mark_cycle_pt(); !block_it.cycled_list(); block_it.forward()) {
block = block_it.data();
make_real_words(textord, block, FCOORD(1.0f, 0.0f));
}
}
/**
* @name set_row_spaces
*
* Set the min_space and max_nonspace members of the row so that
* the blobs can be arranged into words.
*/
void set_row_spaces( //find space sizes
TO_BLOCK *block, //block to do
FCOORD rotation, //for drawing
BOOL8 testing_on //correct orientation
) {
TO_ROW *row; //current row
TO_ROW_IT row_it = block->get_rows ();
if (row_it.empty ())
return; //empty block
for (row_it.mark_cycle_pt (); !row_it.cycled_list (); row_it.forward ()) {
row = row_it.data ();
if (row->fixed_pitch == 0) {
row->min_space =
(inT32) ceil (row->pr_space -
(row->pr_space -
row->pr_nonsp) * textord_words_definite_spread);
row->max_nonspace =
(inT32) floor (row->pr_nonsp +
(row->pr_space -
row->pr_nonsp) * textord_words_definite_spread);
if (testing_on && textord_show_initial_words) {
tprintf ("Assigning defaults %d non, %d space to row at %g\n",
row->max_nonspace, row->min_space, row->intercept ());
}
row->space_threshold = (row->max_nonspace + row->min_space) / 2;
row->space_size = row->pr_space;
row->kern_size = row->pr_nonsp;
}
#ifndef GRAPHICS_DISABLED
if (textord_show_initial_words && testing_on) {
plot_word_decisions (to_win, (inT16) row->fixed_pitch, row);
}
#endif
}
}
/**
* @name row_words
*
* Compute the max nonspace and min space for the row.
*/
inT32 row_words( //compute space size
TO_BLOCK *block, //block it came from
TO_ROW *row, //row to operate on
inT32 maxwidth, //max expected space size
FCOORD rotation, //for drawing
BOOL8 testing_on //for debug
) {
BOOL8 testing_row; //contains testpt
BOOL8 prev_valid; //if decent size
BOOL8 this_valid; //current blob big enough
inT32 prev_x; //end of prev blob
inT32 min_gap; //min interesting gap
inT32 cluster_count; //no of clusters
inT32 gap_index; //which cluster
inT32 smooth_factor; //for smoothing stats
BLOBNBOX *blob; //current blob
float lower, upper; //clustering parameters
float gaps[3]; //gap clusers
ICOORD testpt;
TBOX blob_box; //bounding box
//iterator
BLOBNBOX_IT blob_it = row->blob_list ();
STATS gap_stats (0, maxwidth);
STATS cluster_stats[4]; //clusters
testpt = ICOORD (textord_test_x, textord_test_y);
smooth_factor =
(inT32) (block->xheight * textord_wordstats_smooth_factor + 1.5);
// if (testing_on)
// tprintf("Row smooth factor=%d\n",smooth_factor);
prev_valid = FALSE;
prev_x = -MAX_INT32;
testing_row = FALSE;
for (blob_it.mark_cycle_pt (); !blob_it.cycled_list (); blob_it.forward ()) {
blob = blob_it.data ();
blob_box = blob->bounding_box ();
if (blob_box.contains (testpt))
testing_row = TRUE;
gap_stats.add (blob_box.width (), 1);
}
min_gap = (inT32) floor (gap_stats.ile (textord_words_width_ile));
gap_stats.clear ();
for (blob_it.mark_cycle_pt (); !blob_it.cycled_list (); blob_it.forward ()) {
blob = blob_it.data ();
if (!blob->joined_to_prev ()) {
blob_box = blob->bounding_box ();
// this_valid=blob_box.width()>=min_gap;
this_valid = TRUE;
if (this_valid && prev_valid
&& blob_box.left () - prev_x < maxwidth) {
gap_stats.add (blob_box.left () - prev_x, 1);
}
prev_x = blob_box.right ();
prev_valid = this_valid;
}
}
if (gap_stats.get_total () == 0) {
row->min_space = 0; //no evidence
row->max_nonspace = 0;
return 0;
}
gap_stats.smooth (smooth_factor);
lower = row->xheight * textord_words_initial_lower;
upper = row->xheight * textord_words_initial_upper;
cluster_count = gap_stats.cluster (lower, upper,
textord_spacesize_ratioprop, 3,
cluster_stats);
while (cluster_count < 2 && ceil (lower) < floor (upper)) {
//shrink gap
upper = (upper * 3 + lower) / 4;
lower = (lower * 3 + upper) / 4;
cluster_count = gap_stats.cluster (lower, upper,
textord_spacesize_ratioprop, 3,
cluster_stats);
}
if (cluster_count < 2) {
row->min_space = 0; //no evidence
row->max_nonspace = 0;
return 0;
}
for (gap_index = 0; gap_index < cluster_count; gap_index++)
gaps[gap_index] = cluster_stats[gap_index + 1].ile (0.5);
//get medians
if (cluster_count > 2) {
if (testing_on && textord_show_initial_words) {
tprintf ("Row at %g has 3 sizes of gap:%g,%g,%g\n",
row->intercept (),
cluster_stats[1].ile (0.5),
cluster_stats[2].ile (0.5), cluster_stats[3].ile (0.5));
}
lower = gaps[0];
if (gaps[1] > lower) {
upper = gaps[1]; //prefer most frequent
if (upper < block->xheight * textord_words_min_minspace
&& gaps[2] > gaps[1]) {
upper = gaps[2];
}
}
else if (gaps[2] > lower
&& gaps[2] >= block->xheight * textord_words_min_minspace)
upper = gaps[2];
else if (lower >= block->xheight * textord_words_min_minspace) {
upper = lower; //not nice
lower = gaps[1];
if (testing_on && textord_show_initial_words) {
tprintf ("Had to switch most common from lower to upper!!\n");
gap_stats.print();
}
}
else {
row->min_space = 0; //no evidence
row->max_nonspace = 0;
return 0;
}
}
else {
if (gaps[1] < gaps[0]) {
if (testing_on && textord_show_initial_words) {
tprintf ("Had to switch most common from lower to upper!!\n");
gap_stats.print();
}
lower = gaps[1];
upper = gaps[0];
}
else {
upper = gaps[1];
lower = gaps[0];
}
}
if (upper < block->xheight * textord_words_min_minspace) {
row->min_space = 0; //no evidence
row->max_nonspace = 0;
return 0;
}
if (upper * 3 < block->min_space * 2 + block->max_nonspace
|| lower * 3 > block->min_space * 2 + block->max_nonspace) {
if (testing_on && textord_show_initial_words) {
tprintf ("Disagreement between block and row at %g!!\n",
row->intercept ());
tprintf ("Lower=%g, upper=%g, Stats:\n", lower, upper);
gap_stats.print();
}
}
row->min_space =
(inT32) ceil (upper - (upper - lower) * textord_words_definite_spread);
row->max_nonspace =
(inT32) floor (lower + (upper - lower) * textord_words_definite_spread);
row->space_threshold = (row->max_nonspace + row->min_space) / 2;
row->space_size = upper;
row->kern_size = lower;
if (testing_on && textord_show_initial_words) {
if (testing_row) {
tprintf ("GAP STATS\n");
gap_stats.print();
tprintf ("SPACE stats\n");
cluster_stats[2].print_summary();
tprintf ("NONSPACE stats\n");
cluster_stats[1].print_summary();
}
tprintf ("Row at %g has minspace=%d(%g), max_non=%d(%g)\n",
row->intercept (), row->min_space, upper,
row->max_nonspace, lower);
}
return cluster_stats[2].get_total ();
}
/**
* @name row_words2
*
* Compute the max nonspace and min space for the row.
*/
inT32 row_words2( //compute space size
TO_BLOCK *block, //block it came from
TO_ROW *row, //row to operate on
inT32 maxwidth, //max expected space size
FCOORD rotation, //for drawing
BOOL8 testing_on //for debug
) {
BOOL8 testing_row; //contains testpt
BOOL8 prev_valid; //if decent size
BOOL8 this_valid; //current blob big enough
inT32 prev_x; //end of prev blob
inT32 min_width; //min interesting width
inT32 valid_count; //good gaps
inT32 total_count; //total gaps
inT32 cluster_count; //no of clusters
inT32 prev_count; //previous cluster_count
inT32 gap_index; //which cluster
inT32 smooth_factor; //for smoothing stats
BLOBNBOX *blob; //current blob
float lower, upper; //clustering parameters
ICOORD testpt;
TBOX blob_box; //bounding box
//iterator
BLOBNBOX_IT blob_it = row->blob_list ();
STATS gap_stats (0, maxwidth);
//gap sizes
float gaps[BLOCK_STATS_CLUSTERS];
STATS cluster_stats[BLOCK_STATS_CLUSTERS + 1];
//clusters
testpt = ICOORD (textord_test_x, textord_test_y);
smooth_factor =
(inT32) (block->xheight * textord_wordstats_smooth_factor + 1.5);
// if (testing_on)
// tprintf("Row smooth factor=%d\n",smooth_factor);
prev_valid = FALSE;
prev_x = -MAX_INT16;
testing_row = FALSE;
//min blob size
min_width = (inT32) block->pr_space;
total_count = 0;
for (blob_it.mark_cycle_pt (); !blob_it.cycled_list (); blob_it.forward ()) {
blob = blob_it.data ();
if (!blob->joined_to_prev ()) {
blob_box = blob->bounding_box ();
this_valid = blob_box.width () >= min_width;
if (this_valid && prev_valid
&& blob_box.left () - prev_x < maxwidth) {
gap_stats.add (blob_box.left () - prev_x, 1);
}
total_count++; //count possibles
prev_x = blob_box.right ();
prev_valid = this_valid;
}
}
valid_count = gap_stats.get_total ();
if (valid_count < total_count * textord_words_minlarge) {
gap_stats.clear ();
prev_x = -MAX_INT16;
for (blob_it.mark_cycle_pt (); !blob_it.cycled_list ();
blob_it.forward ()) {
blob = blob_it.data ();
if (!blob->joined_to_prev ()) {
blob_box = blob->bounding_box ();
if (blob_box.left () - prev_x < maxwidth) {
gap_stats.add (blob_box.left () - prev_x, 1);
}
prev_x = blob_box.right ();
}
}
}
if (gap_stats.get_total () == 0) {
row->min_space = 0; //no evidence
row->max_nonspace = 0;
return 0;
}
cluster_count = 0;
lower = block->xheight * words_initial_lower;
upper = block->xheight * words_initial_upper;
gap_stats.smooth (smooth_factor);
do {
prev_count = cluster_count;
cluster_count = gap_stats.cluster (lower, upper,
textord_spacesize_ratioprop,
BLOCK_STATS_CLUSTERS, cluster_stats);
}
while (cluster_count > prev_count && cluster_count < BLOCK_STATS_CLUSTERS);
if (cluster_count < 1) {
row->min_space = 0;
row->max_nonspace = 0;
return 0;
}
for (gap_index = 0; gap_index < cluster_count; gap_index++)
gaps[gap_index] = cluster_stats[gap_index + 1].ile (0.5);
//get medians
if (testing_on) {
tprintf ("cluster_count=%d:", cluster_count);
for (gap_index = 0; gap_index < cluster_count; gap_index++)
tprintf (" %g(%d)", gaps[gap_index],
cluster_stats[gap_index + 1].get_total ());
tprintf ("\n");
}
//Try to find proportional non-space and space for row.
for (gap_index = 0; gap_index < cluster_count
&& gaps[gap_index] > block->max_nonspace; gap_index++);
if (gap_index < cluster_count)
lower = gaps[gap_index]; //most frequent below
else {
if (testing_on)
tprintf ("No cluster below block threshold!, using default=%g\n",
block->pr_nonsp);
lower = block->pr_nonsp;
}
for (gap_index = 0; gap_index < cluster_count
&& gaps[gap_index] <= block->max_nonspace; gap_index++);
if (gap_index < cluster_count)
upper = gaps[gap_index]; //most frequent above
else {
if (testing_on)
tprintf ("No cluster above block threshold!, using default=%g\n",
block->pr_space);
upper = block->pr_space;
}
row->min_space =
(inT32) ceil (upper - (upper - lower) * textord_words_definite_spread);
row->max_nonspace =
(inT32) floor (lower + (upper - lower) * textord_words_definite_spread);
row->space_threshold = (row->max_nonspace + row->min_space) / 2;
row->space_size = upper;
row->kern_size = lower;
if (testing_on) {
if (testing_row) {
tprintf ("GAP STATS\n");
gap_stats.print();
tprintf ("SPACE stats\n");
cluster_stats[2].print_summary();
tprintf ("NONSPACE stats\n");
cluster_stats[1].print_summary();
}
tprintf ("Row at %g has minspace=%d(%g), max_non=%d(%g)\n",
row->intercept (), row->min_space, upper,
row->max_nonspace, lower);
}
return 1;
}
/**
* @name make_real_words
*
* Convert a TO_BLOCK to a BLOCK.
*/
void make_real_words(
tesseract::Textord *textord,
TO_BLOCK *block, //block to do
FCOORD rotation //for drawing
) {
TO_ROW *row; //current row
TO_ROW_IT row_it = block->get_rows ();
ROW *real_row = NULL; //output row
ROW_IT real_row_it = block->block->row_list ();
if (row_it.empty ())
return; //empty block
for (row_it.mark_cycle_pt (); !row_it.cycled_list (); row_it.forward ()) {
row = row_it.data ();
if (row->blob_list ()->empty () && !row->rep_words.empty ()) {
real_row = make_rep_words (row, block);
} else if (!row->blob_list()->empty()) {
// In a fixed pitch document, some lines may be detected as fixed pitch
// while others don't, and will go through different path.
// For non-space delimited language like CJK, fixed pitch chop always
// leave the entire line as one word. We can force consistent chopping
// with force_make_prop_words flag.
POLY_BLOCK* pb = block->block->poly_block();
if (textord_chopper_test) {
real_row = textord->make_blob_words (row, rotation);
} else if (textord_force_make_prop_words ||
(pb != NULL && !pb->IsText()) ||
row->pitch_decision == PITCH_DEF_PROP ||
row->pitch_decision == PITCH_CORR_PROP) {
real_row = textord->make_prop_words (row, rotation);
} else if (row->pitch_decision == PITCH_DEF_FIXED ||
row->pitch_decision == PITCH_CORR_FIXED) {
real_row = fixed_pitch_words (row, rotation);
} else {
ASSERT_HOST(FALSE);
}
}
if (real_row != NULL) {
//put row in block
real_row_it.add_after_then_move (real_row);
}
}
block->block->set_stats (block->fixed_pitch == 0, (inT16) block->kern_size,
(inT16) block->space_size,
(inT16) block->fixed_pitch);
block->block->check_pitch ();
}
/**
* @name make_rep_words
*
* Fabricate a real row from only the repeated blob words.
* Get the xheight from the block as it may be more meaningful.
*/
ROW *make_rep_words( //make a row
TO_ROW *row, //row to convert
TO_BLOCK *block //block it lives in
) {
ROW *real_row; //output row
TBOX word_box; //bounding box
//iterator
WERD_IT word_it = &row->rep_words;
if (word_it.empty ())
return NULL;
word_box = word_it.data ()->bounding_box ();
for (word_it.mark_cycle_pt (); !word_it.cycled_list (); word_it.forward ())
word_box += word_it.data ()->bounding_box ();
row->xheight = block->xheight;
real_row = new ROW(row,
(inT16) block->kern_size, (inT16) block->space_size);
word_it.set_to_list (real_row->word_list ());
//put words in row
word_it.add_list_after (&row->rep_words);
real_row->recalc_bounding_box ();
return real_row;
}
/**
* @name make_real_word
*
* Construct a WERD from a given number of adjacent entries in a
* list of BLOBNBOXs.
*/
WERD *make_real_word(BLOBNBOX_IT *box_it, //iterator
inT32 blobcount, //no of blobs to use
BOOL8 bol, //start of line
uinT8 blanks //no of blanks
) {
C_OUTLINE_IT cout_it;
C_BLOB_LIST cblobs;
C_BLOB_IT cblob_it = &cblobs;
WERD *word; // new word
BLOBNBOX *bblob; // current blob
inT32 blobindex; // in row
for (blobindex = 0; blobindex < blobcount; blobindex++) {
bblob = box_it->extract();
if (bblob->joined_to_prev()) {
if (bblob->cblob() != NULL) {
cout_it.set_to_list(cblob_it.data()->out_list());
cout_it.move_to_last();
cout_it.add_list_after(bblob->cblob()->out_list());
delete bblob->cblob();
}
}
else {
if (bblob->cblob() != NULL)
cblob_it.add_after_then_move(bblob->cblob());
}
delete bblob;
box_it->forward(); // next one
}
if (blanks < 1)
blanks = 1;
word = new WERD(&cblobs, blanks, NULL);
if (bol)
word->set_flag(W_BOL, TRUE);
if (box_it->at_first())
word->set_flag(W_EOL, TRUE); // at end of line
return word;
}
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