tesseract/textord/devanagari_processing.cpp

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/**********************************************************************
* File: devanagari_processing.cpp
* Description: Methods to process images containing devanagari symbols,
* prior to classification.
* Author: Shobhit Saxena
* Created: Mon Nov 17 20:26:01 IST 2008
*
* (C) Copyright 2008, Google Inc.
** 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.
*
**********************************************************************/
#include "devanagari_processing.h"
#include "allheaders.h"
#include "tordmain.h"
#include "statistc.h"
// Flags controlling the debugging information for shiro-rekha splitting
// strategies.
INT_VAR(devanagari_split_debuglevel, 0,
"Debug level for split shiro-rekha process.");
BOOL_VAR(devanagari_split_debugimage, 0,
"Whether to create a debug image for split shiro-rekha process.");
namespace tesseract {
ShiroRekhaSplitter::ShiroRekhaSplitter() {
orig_pix_ = NULL;
segmentation_block_list_ = NULL;
splitted_image_ = NULL;
global_xheight_ = kUnspecifiedXheight;
perform_close_ = false;
debug_image_ = NULL;
pageseg_split_strategy_ = NO_SPLIT;
ocr_split_strategy_ = NO_SPLIT;
}
ShiroRekhaSplitter::~ShiroRekhaSplitter() {
Clear();
}
void ShiroRekhaSplitter::Clear() {
pixDestroy(&orig_pix_);
pixDestroy(&splitted_image_);
pageseg_split_strategy_ = NO_SPLIT;
ocr_split_strategy_ = NO_SPLIT;
pixDestroy(&debug_image_);
segmentation_block_list_ = NULL;
global_xheight_ = kUnspecifiedXheight;
perform_close_ = false;
}
// This method dumps a debug image to the specified location.
void ShiroRekhaSplitter::DumpDebugImage(const char* filename) const {
pixWrite(filename, debug_image_, IFF_PNG);
}
// On setting the input image, a clone of it is owned by this class.
void ShiroRekhaSplitter::set_orig_pix(Pix* pix) {
if (orig_pix_) {
pixDestroy(&orig_pix_);
}
orig_pix_ = pixClone(pix);
}
// Top-level method to perform splitting based on current settings.
// Returns true if a split was actually performed.
// split_for_pageseg should be true if the splitting is being done prior to
// page segmentation. This mode uses the flag
// pageseg_devanagari_split_strategy to determine the splitting strategy.
bool ShiroRekhaSplitter::Split(bool split_for_pageseg) {
SplitStrategy split_strategy = split_for_pageseg ? pageseg_split_strategy_ :
ocr_split_strategy_;
if (split_strategy == NO_SPLIT) {
return false; // Nothing to do.
}
ASSERT_HOST(split_strategy == MINIMAL_SPLIT ||
split_strategy == MAXIMAL_SPLIT);
ASSERT_HOST(orig_pix_);
if (devanagari_split_debuglevel > 0) {
tprintf("Splitting shiro-rekha ...\n");
tprintf("Split strategy = %s\n",
split_strategy == MINIMAL_SPLIT ? "Minimal" : "Maximal");
tprintf("Initial pageseg available = %s\n",
segmentation_block_list_ ? "yes" : "no");
}
// Create a copy of original image to store the splitting output.
pixDestroy(&splitted_image_);
splitted_image_ = pixCopy(NULL, orig_pix_);
// Initialize debug image if required.
if (devanagari_split_debugimage) {
pixDestroy(&debug_image_);
debug_image_ = pixConvertTo32(orig_pix_);
}
// Determine all connected components in the input image. A close operation
// may be required prior to this, depending on the current settings.
Pix* pix_for_ccs = pixClone(orig_pix_);
if (perform_close_ && global_xheight_ != kUnspecifiedXheight &&
!segmentation_block_list_) {
if (devanagari_split_debuglevel > 0) {
tprintf("Performing a global close operation..\n");
}
// A global measure is available for xheight, but no local information
// exists.
pixDestroy(&pix_for_ccs);
pix_for_ccs = pixCopy(NULL, orig_pix_);
PerformClose(pix_for_ccs, global_xheight_);
}
Pixa* ccs;
Boxa* tmp_boxa = pixConnComp(pix_for_ccs, &ccs, 8);
boxaDestroy(&tmp_boxa);
pixDestroy(&pix_for_ccs);
// Iterate over all connected components. Get their bounding boxes and clip
// out the image regions corresponding to these boxes from the original image.
// Conditionally run splitting on each of them.
Boxa* regions_to_clear = boxaCreate(0);
for (int i = 0; i < pixaGetCount(ccs); ++i) {
Box* box = ccs->boxa->box[i];
Pix* word_pix = pixClipRectangle(orig_pix_, box, NULL);
ASSERT_HOST(word_pix);
int xheight = GetXheightForCC(box);
if (xheight == kUnspecifiedXheight && segmentation_block_list_ &&
devanagari_split_debugimage) {
pixRenderBoxArb(debug_image_, box, 1, 255, 0, 0);
}
// If some xheight measure is available, attempt to pre-eliminate small
// blobs from the shiro-rekha process. This is primarily to save the CCs
// corresponding to punctuation marks/small dots etc which are part of
// larger graphemes.
if (xheight == kUnspecifiedXheight ||
(box->w > xheight / 3 && box->h > xheight / 2)) {
SplitWordShiroRekha(split_strategy, word_pix, xheight,
box->x, box->y, regions_to_clear);
} else if (devanagari_split_debuglevel > 0) {
tprintf("CC dropped from splitting: %d,%d (%d, %d)\n",
box->x, box->y, box->w, box->h);
}
pixDestroy(&word_pix);
}
// Actually clear the boxes now.
for (int i = 0; i < boxaGetCount(regions_to_clear); ++i) {
Box* box = boxaGetBox(regions_to_clear, i, L_CLONE);
pixClearInRect(splitted_image_, box);
boxDestroy(&box);
}
boxaDestroy(&regions_to_clear);
pixaDestroy(&ccs);
if (devanagari_split_debugimage) {
DumpDebugImage(split_for_pageseg ? "pageseg_split_debug.png" :
"ocr_split_debug.png");
}
return true;
}
// Method to perform a close operation on the input image. The xheight
// estimate decides the size of sel used.
void ShiroRekhaSplitter::PerformClose(Pix* pix, int xheight_estimate) {
pixCloseBrick(pix, pix, xheight_estimate / 8, xheight_estimate / 3);
}
// This method resolves the cc bbox to a particular row and returns the row's
// xheight.
int ShiroRekhaSplitter::GetXheightForCC(Box* cc_bbox) {
if (!segmentation_block_list_) {
return global_xheight_;
}
// Compute the box coordinates in Tesseract's coordinate system.
TBOX bbox(cc_bbox->x,
pixGetHeight(orig_pix_) - cc_bbox->y - cc_bbox->h - 1,
cc_bbox->x + cc_bbox->w,
pixGetHeight(orig_pix_) - cc_bbox->y - 1);
// Iterate over all blocks.
BLOCK_IT block_it(segmentation_block_list_);
for (block_it.mark_cycle_pt(); !block_it.cycled_list(); block_it.forward()) {
BLOCK* block = block_it.data();
// Iterate over all rows in the block.
ROW_IT row_it(block->row_list());
for (row_it.mark_cycle_pt(); !row_it.cycled_list(); row_it.forward()) {
ROW* row = row_it.data();
if (!row->bounding_box().major_overlap(bbox)) {
continue;
}
// Row could be skewed, warped, etc. Use the position of the box to
// determine the baseline position of the row for that x-coordinate.
// Create a square TBOX whose baseline's mid-point lies at this point
// and side is row's xheight. Take the overlap of this box with the input
// box and check if it is a 'major overlap'. If so, this box lies in this
// row. In that case, return the xheight for this row.
float box_middle = 0.5 * (bbox.left() + bbox.right());
int baseline = static_cast<int>(row->base_line(box_middle) + 0.5);
TBOX test_box(box_middle - row->x_height() / 2,
baseline,
box_middle + row->x_height() / 2,
static_cast<int>(baseline + row->x_height()));
// Compute overlap. If it is is a major overlap, this is the right row.
if (bbox.major_overlap(test_box)) {
return row->x_height();
}
}
}
// No row found for this bbox.
return kUnspecifiedXheight;
}
// Returns a list of regions (boxes) which should be cleared in the original
// image so as to perform shiro-rekha splitting. Pix is assumed to carry one
// (or less) word only. Xheight measure could be the global estimate, the row
// estimate, or unspecified. If unspecified, over splitting may occur, since a
// conservative estimate of stroke width along with an associated multiplier
// is used in its place. It is advisable to have a specified xheight when
// splitting for classification/training.
// A vertical projection histogram of all the on-pixels in the input pix is
// computed. The maxima of this histogram is regarded as an approximate location
// of the shiro-rekha. By descending on the maxima's peak on both sides,
// stroke width of shiro-rekha is estimated.
// A horizontal projection histogram is computed for a sub-image of the input
// image, which extends from just below the shiro-rekha down to a certain
// leeway. The leeway depends on the input xheight, if provided, else a
// conservative multiplier on approximate stroke width is used (which may lead
// to over-splitting).
void ShiroRekhaSplitter::SplitWordShiroRekha(SplitStrategy split_strategy,
Pix* pix,
int xheight,
int word_left,
int word_top,
Boxa* regions_to_clear) {
if (split_strategy == NO_SPLIT) {
return;
}
int width = pixGetWidth(pix);
int height = pixGetHeight(pix);
// Statistically determine the yextents of the shiro-rekha.
int shirorekha_top, shirorekha_bottom, shirorekha_ylevel;
GetShiroRekhaYExtents(pix, &shirorekha_top, &shirorekha_bottom,
&shirorekha_ylevel);
// Since the shiro rekha is also a stroke, its width is equal to the stroke
// width.
int stroke_width = shirorekha_bottom - shirorekha_top + 1;
// Some safeguards to protect CCs we do not want to be split.
// These are particularly useful when the word wasn't eliminated earlier
// because xheight information was unavailable.
if (shirorekha_ylevel > height / 2) {
// Shirorekha shouldn't be in the bottom half of the word.
if (devanagari_split_debuglevel > 0) {
tprintf("Skipping splitting CC at (%d, %d): shirorekha in lower half..\n",
word_left, word_top);
}
return;
}
if (stroke_width > height / 3) {
// Even the boldest of fonts shouldn't do this.
if (devanagari_split_debuglevel > 0) {
tprintf("Skipping splitting CC at (%d, %d): stroke width too huge..\n",
word_left, word_top);
}
return;
}
// Clear the ascender and descender regions of the word.
// Obtain a vertical projection histogram for the resulting image.
Box* box_to_clear = boxCreate(0, shirorekha_top - stroke_width / 3,
width, 5 * stroke_width / 3);
Pix* word_in_xheight = pixCopy(NULL, pix);
pixClearInRect(word_in_xheight, box_to_clear);
// Also clear any pixels which are below shirorekha_bottom + some leeway.
// The leeway is set to xheight if the information is available, else it is a
// multiplier applied to the stroke width.
int leeway_to_keep = stroke_width * 3;
if (xheight != kUnspecifiedXheight) {
// This is because the xheight-region typically includes the shiro-rekha
// inside it, i.e., the top of the xheight range corresponds to the top of
// shiro-rekha.
leeway_to_keep = xheight - stroke_width;
}
box_to_clear->y = shirorekha_bottom + leeway_to_keep;
box_to_clear->h = height - box_to_clear->y;
pixClearInRect(word_in_xheight, box_to_clear);
boxDestroy(&box_to_clear);
PixelHistogram vert_hist;
vert_hist.ConstructVerticalCountHist(word_in_xheight);
pixDestroy(&word_in_xheight);
// If the number of black pixel in any column of the image is less than a
// fraction of the stroke width, treat it as noise / a stray mark. Perform
// these changes inside the vert_hist data itself, as that is used later on as
// a bit vector for the final split decision at every column.
for (int i = 0; i < width; ++i) {
if (vert_hist.hist()[i] <= stroke_width / 4)
vert_hist.hist()[i] = 0;
else
vert_hist.hist()[i] = 1;
}
// In order to split the line at any point, we make sure that the width of the
// gap is atleast half the stroke width.
int i = 0;
int cur_component_width = 0;
while (i < width) {
if (!vert_hist.hist()[i]) {
int j = 0;
while (i + j < width && !vert_hist.hist()[i+j])
++j;
if (j >= stroke_width / 2 && cur_component_width >= stroke_width / 2) {
// Perform a shiro-rekha split. The intervening region lies from i to
// i+j-1.
// A minimal single-pixel split makes the estimation of intra- and
// inter-word spacing easier during page layout analysis,
// whereas a maximal split may be needed for OCR, depending on
// how the engine was trained.
bool minimal_split = (split_strategy == MINIMAL_SPLIT);
int split_width = minimal_split ? 1 : j;
int split_left = minimal_split ? i + (j / 2) - (split_width / 2) : i;
if (!minimal_split || (i != 0 && i + j != width)) {
Box* box_to_clear =
boxCreate(word_left + split_left,
word_top + shirorekha_top - stroke_width / 3,
split_width,
5 * stroke_width / 3);
if (box_to_clear) {
boxaAddBox(regions_to_clear, box_to_clear, L_CLONE);
// Mark this in the debug image if needed.
if (devanagari_split_debugimage) {
pixRenderBoxArb(debug_image_, box_to_clear, 1, 128, 255, 128);
}
boxDestroy(&box_to_clear);
cur_component_width = 0;
}
}
}
i += j;
} else {
++i;
++cur_component_width;
}
}
}
// Refreshes the words in the segmentation block list by using blobs in the
// input block list.
// The segmentation block list must be set.
void ShiroRekhaSplitter::RefreshSegmentationWithNewBlobs(
C_BLOB_LIST* new_blobs) {
// The segmentation block list must have been specified.
ASSERT_HOST(segmentation_block_list_);
if (devanagari_split_debuglevel > 0) {
tprintf("Before refreshing blobs:\n");
PrintSegmentationStats(segmentation_block_list_);
tprintf("New Blobs found: %d\n", new_blobs->length());
}
C_BLOB_LIST not_found_blobs;
RefreshWordBlobsFromNewBlobs(segmentation_block_list_,
new_blobs,
((devanagari_split_debugimage && debug_image_) ?
&not_found_blobs : NULL));
if (devanagari_split_debuglevel > 0) {
tprintf("After refreshing blobs:\n");
PrintSegmentationStats(segmentation_block_list_);
}
if (devanagari_split_debugimage && debug_image_) {
// Plot out the original blobs for which no match was found in the new
// all_blobs list.
C_BLOB_IT not_found_it(&not_found_blobs);
for (not_found_it.mark_cycle_pt(); !not_found_it.cycled_list();
not_found_it.forward()) {
C_BLOB* not_found = not_found_it.data();
TBOX not_found_box = not_found->bounding_box();
Box* box_to_plot = GetBoxForTBOX(not_found_box);
pixRenderBoxArb(debug_image_, box_to_plot, 1, 255, 0, 255);
boxDestroy(&box_to_plot);
}
// Plot out the blobs unused from all blobs.
C_BLOB_IT all_blobs_it(new_blobs);
for (all_blobs_it.mark_cycle_pt(); !all_blobs_it.cycled_list();
all_blobs_it.forward()) {
C_BLOB* a_blob = all_blobs_it.data();
Box* box_to_plot = GetBoxForTBOX(a_blob->bounding_box());
pixRenderBoxArb(debug_image_, box_to_plot, 3, 0, 127, 0);
boxDestroy(&box_to_plot);
}
}
}
// Returns a new box object for the corresponding TBOX, based on the original
// image's coordinate system.
Box* ShiroRekhaSplitter::GetBoxForTBOX(const TBOX& tbox) const {
return boxCreate(tbox.left(), pixGetHeight(orig_pix_) - tbox.top() - 1,
tbox.width(), tbox.height());
}
// This method returns the computed mode-height of blobs in the pix.
// It also prunes very small blobs from calculation.
int ShiroRekhaSplitter::GetModeHeight(Pix* pix) {
Boxa* boxa = pixConnComp(pix, NULL, 8);
STATS heights(0, pixGetHeight(pix));
heights.clear();
for (int i = 0; i < boxaGetCount(boxa); ++i) {
Box* box = boxaGetBox(boxa, i, L_CLONE);
if (box->h >= 3 || box->w >= 3) {
heights.add(box->h, 1);
}
boxDestroy(&box);
}
boxaDestroy(&boxa);
return heights.mode();
}
// This method returns y-extents of the shiro-rekha computed from the input
// word image.
void ShiroRekhaSplitter::GetShiroRekhaYExtents(Pix* word_pix,
int* shirorekha_top,
int* shirorekha_bottom,
int* shirorekha_ylevel) {
// Compute a histogram from projecting the word on a vertical line.
PixelHistogram hist_horiz;
hist_horiz.ConstructHorizontalCountHist(word_pix);
// Get the ylevel where the top-line exists. This is basically the global
// maxima in the horizontal histogram.
int topline_onpixel_count = 0;
int topline_ylevel = hist_horiz.GetHistogramMaximum(&topline_onpixel_count);
// Get the upper and lower extents of the shiro rekha.
int thresh = (topline_onpixel_count * 70) / 100;
int ulimit = topline_ylevel;
int llimit = topline_ylevel;
while (ulimit > 0 && hist_horiz.hist()[ulimit] >= thresh)
--ulimit;
while (llimit < word_pix->h && hist_horiz.hist()[llimit] >= thresh)
++llimit;
if (shirorekha_top) *shirorekha_top = ulimit;
if (shirorekha_bottom) *shirorekha_bottom = llimit;
if (shirorekha_ylevel) *shirorekha_ylevel = topline_ylevel;
}
// This method returns the global-maxima for the histogram. The frequency of
// the global maxima is returned in count, if specified.
int PixelHistogram::GetHistogramMaximum(int* count) const {
int best_value = 0;
for (int i = 0; i < length_; ++i) {
if (hist_[i] > hist_[best_value]) {
best_value = i;
}
}
if (count) {
*count = hist_[best_value];
}
return best_value;
}
// Methods to construct histograms from images.
void PixelHistogram::ConstructVerticalCountHist(Pix* pix) {
Clear();
int width = pixGetWidth(pix);
int height = pixGetHeight(pix);
hist_ = new int[width];
length_ = width;
int wpl = pixGetWpl(pix);
l_uint32 *data = pixGetData(pix);
for (int i = 0; i < width; ++i)
hist_[i] = 0;
for (int i = 0; i < height; ++i) {
l_uint32 *line = data + i * wpl;
for (int j = 0; j < width; ++j)
if (GET_DATA_BIT(line, j))
++(hist_[j]);
}
}
void PixelHistogram::ConstructHorizontalCountHist(Pix* pix) {
Clear();
Numa* counts = pixCountPixelsByRow(pix, NULL);
length_ = numaGetCount(counts);
hist_ = new int[length_];
for (int i = 0; i < length_; ++i) {
l_int32 val = 0;
numaGetIValue(counts, i, &val);
hist_[i] = val;
}
numaDestroy(&counts);
}
} // namespace tesseract.