tesseract/wordrec/heuristic.cpp

195 lines
6.1 KiB
C++
Raw Normal View History

/* -*-C-*-
********************************************************************************
*
* File: heuristic.c (Formerly heuristic.c)
* Description:
* Author: Mark Seaman, OCR Technology
* Created: Fri Oct 16 14:37:00 1987
* Modified: Wed Jul 10 14:15:08 1991 (Mark Seaman) marks@hpgrlt
* Language: C
* Package: N/A
* Status: Reusable Software Component
*
* (c) Copyright 1987, Hewlett-Packard Company.
** 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.
*
*********************************************************************************/
/*----------------------------------------------------------------------
I n c l u d e s
----------------------------------------------------------------------*/
#include "heuristic.h"
#include "baseline.h"
#include "metrics.h"
#include "freelist.h"
#include <math.h>
/*----------------------------------------------------------------------
M a c r o s
----------------------------------------------------------------------*/
#define MAX_SQUAT 2.0 /* Width ratio */
#define BAD_RATING 1000.0 /* No valid blob */
/*----------------------------------------------------------------------
F u n c t i o n s
----------------------------------------------------------------------*/
/**********************************************************************
* prioritize_state
*
* Create a priority for this state. It represents the urgency of
* checking this state.
**********************************************************************/
FLOAT32 prioritize_state(CHUNKS_RECORD *chunks_record,
SEARCH_RECORD *the_search,
STATE *old_state) {
FLOAT32 width_pri;
FLOAT32 match_pri;
match_pri = rating_priority (chunks_record, the_search->this_state,
old_state, the_search->num_joints);
width_pri = width_priority (chunks_record, the_search->this_state,
the_search->num_joints) * 1000.0;
record_priorities(the_search, old_state, match_pri, width_pri);
return (width_pri + match_pri);
}
/**********************************************************************
* rating_priority
*
* Assign a segmentation priority based on the ratings of the blobs
* (in that segmentation) that have been classified. The average
* "goodness" (i.e. rating / weight) for each blob is used to indicate
* the segmentation priority.
**********************************************************************/
FLOAT32 rating_priority(CHUNKS_RECORD *chunks_record,
STATE *state,
STATE *old_state,
int num_joints) {
PIECES_STATE blob_chunks;
INT16 x;
INT16 y;
CHOICES this_choice;
INT16 first_chunk = 0;
INT16 last_chunk;
INT16 ratings = 0;
INT16 weights = 0;
bin_to_pieces(state, num_joints, blob_chunks);
for (x = 0; blob_chunks[x]; x++) {
// Iterate each blob
last_chunk = first_chunk + blob_chunks[x] - 1;
this_choice = matrix_get (chunks_record->ratings,
first_chunk, last_chunk);
if (this_choice == NIL)
return (BAD_RATING);
if (this_choice != NOT_CLASSIFIED) {
ratings += (INT16) best_probability (this_choice);
for (y = first_chunk; y <= last_chunk; y++) {
weights += (INT16) (chunks_record->weights[y]);
}
}
first_chunk += blob_chunks[x];
}
if (weights <= 0)
weights = 1;
return ((FLOAT32) ratings / weights);
}
/**********************************************************************
* state_char_widths
*
* Return a character width record corresponding to the character
* width that will be generated in this segmentation state.
**********************************************************************/
WIDTH_RECORD *state_char_widths(WIDTH_RECORD *chunk_widths,
STATE *state,
int num_joints,
SEARCH_STATE *search_state) {
WIDTH_RECORD *width_record;
int num_blobs;
int x;
int y;
int i;
SEARCH_STATE new_chunks;
new_chunks = bin_to_chunks (state, num_joints);
num_blobs = new_chunks[0] + 1;
width_record = (WIDTH_RECORD *) memalloc (sizeof (int) * num_blobs * 2);
width_record->num_chars = num_blobs;
x = 0;
for (i = 1; i <= new_chunks[0] + 1; i++) {
if (i > new_chunks[0])
y = num_joints;
else
y = x + new_chunks[i];
width_record->widths[2 * i - 2] = chunks_width (chunk_widths, x, y);
if (i <= new_chunks[0])
width_record->widths[2 * i - 1] = chunks_gap (chunk_widths, y);
x = y + 1;
}
*search_state = new_chunks;
return (width_record);
}
/**********************************************************************
* width_priority
*
* Return a priority value for this word segmentation based on the
* character widths present in the new segmentation.
**********************************************************************/
FLOAT32 width_priority(CHUNKS_RECORD *chunks_record,
STATE *state,
int num_joints) {
SEARCH_STATE new_chunks;
FLOAT32 result = 0.0;
WIDTH_RECORD *width_record;
FLOAT32 squat;
int x;
width_record = state_char_widths (chunks_record->chunk_widths,
state, num_joints, &new_chunks);
for (x = 0; x < width_record->num_chars; x++) {
squat = width_record->widths[2 * x];
if (!baseline_enable) {
squat /= chunks_record->row->lineheight;
}
else {
squat /= BASELINE_SCALE;
}
if (squat > MAX_SQUAT)
result += squat - MAX_SQUAT;
}
memfree(new_chunks);
free_widths(width_record);
return (result);
}