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+/**********************************************************************
+ * File: fixxht.cpp (Formerly fixxht.c)
+ * Description: Improve x_ht and look out for case inconsistencies
+ * Author: Phil Cheatle
+ * Created: Thu Aug 5 14:11:08 BST 1993
+ *
+ * (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.
+ *
+ **********************************************************************/
+
+#include "params.h"
+#include "float2int.h"
+#include "tesseractclass.h"
+
+#include <algorithm>
+#include <cstring>
+#include <cctype>
+
+namespace tesseract {
+
+// Fixxht overview.
+// Premise: Initial estimate of x-height is adequate most of the time, but
+// occasionally it is incorrect. Most notable causes of failure are:
+// 1. Small caps, where the top of the caps is the same as the body text
+// xheight. For small caps words the xheight needs to be reduced to correctly
+// recognize the caps in the small caps word.
+// 2. All xheight lines, such as summer. Here the initial estimate will have
+// guessed that the blob tops are caps and will have placed the xheight too low.
+// 3. Noise/logos beside words, or changes in font size on a line. Such
+// things can blow the statistics and cause an incorrect estimate.
+// 4. Incorrect baseline. Can happen when 2 columns are incorrectly merged.
+// In this case the x-height is often still correct.
+//
+// Algorithm.
+// Compare the vertical position (top only) of alphnumerics in a word with
+// the range of positions in training data (in the unicharset).
+// See CountMisfitTops. If any characters disagree sufficiently with the
+// initial xheight estimate, then recalculate the xheight, re-run OCR on
+// the word, and if the number of vertical misfits goes down, along with
+// either the word rating or certainty, then keep the new xheight.
+// The new xheight is calculated as follows:ComputeCompatibleXHeight
+// For each alphanumeric character that has a vertically misplaced top
+// (a misfit), yet its bottom is within the acceptable range (ie it is not
+// likely a sub-or super-script) calculate the range of acceptable xheight
+// positions from its range of tops, and give each value in the range a
+// number of votes equal to the distance of its top from its acceptance range.
+// The x-height position with the median of the votes becomes the new
+// x-height. This assumes that most characters will be correctly recognized
+// even if the x-height is incorrect. This is not a terrible assumption, but
+// it is not great. An improvement would be to use a classifier that does
+// not care about vertical position or scaling at all.
+// Separately collect stats on shifted baselines and apply the same logic to
+// computing a best-fit shift to fix the error. If the baseline needs to be
+// shifted, but the x-height is OK, returns the original x-height along with
+// the baseline shift to indicate that recognition needs to re-run.
+
+// If the max-min top of a unicharset char is bigger than kMaxCharTopRange
+// then the char top cannot be used to judge misfits or suggest a new top.
+const int kMaxCharTopRange = 48;
+
+// Returns the number of misfit blob tops in this word.
+int Tesseract::CountMisfitTops(WERD_RES *word_res) {
+ int bad_blobs = 0;
+ int num_blobs = word_res->rebuild_word->NumBlobs();
+ for (int blob_id = 0; blob_id < num_blobs; ++blob_id) {
+ TBLOB* blob = word_res->rebuild_word->blobs[blob_id];
+ UNICHAR_ID class_id = word_res->best_choice->unichar_id(blob_id);
+ if (unicharset.get_isalpha(class_id) || unicharset.get_isdigit(class_id)) {
+ int top = blob->bounding_box().top();
+ if (top >= INT_FEAT_RANGE)
+ top = INT_FEAT_RANGE - 1;
+ int min_bottom, max_bottom, min_top, max_top;
+ unicharset.get_top_bottom(class_id, &min_bottom, &max_bottom,
+ &min_top, &max_top);
+ if (max_top - min_top > kMaxCharTopRange)
+ continue;
+ bool bad = top < min_top - x_ht_acceptance_tolerance ||
+ top > max_top + x_ht_acceptance_tolerance;
+ if (bad)
+ ++bad_blobs;
+ if (debug_x_ht_level >= 1) {
+ tprintf("Class %s is %s with top %d vs limits of %d->%d, +/-%d\n",
+ unicharset.id_to_unichar(class_id),
+ bad ? "Misfit" : "OK", top, min_top, max_top,
+ static_cast<int>(x_ht_acceptance_tolerance));
+ }
+ }
+ }
+ return bad_blobs;
+}
+
+// Returns a new x-height maximally compatible with the result in word_res.
+// See comment above for overall algorithm.
+float Tesseract::ComputeCompatibleXheight(WERD_RES *word_res,
+ float* baseline_shift) {
+ STATS top_stats(0, UINT8_MAX);
+ STATS shift_stats(-UINT8_MAX, UINT8_MAX);
+ int bottom_shift = 0;
+ int num_blobs = word_res->rebuild_word->NumBlobs();
+ do {
+ top_stats.clear();
+ shift_stats.clear();
+ for (int blob_id = 0; blob_id < num_blobs; ++blob_id) {
+ TBLOB* blob = word_res->rebuild_word->blobs[blob_id];
+ UNICHAR_ID class_id = word_res->best_choice->unichar_id(blob_id);
+ if (unicharset.get_isalpha(class_id) ||
+ unicharset.get_isdigit(class_id)) {
+ int top = blob->bounding_box().top() + bottom_shift;
+ // Clip the top to the limit of normalized feature space.
+ if (top >= INT_FEAT_RANGE)
+ top = INT_FEAT_RANGE - 1;
+ int bottom = blob->bounding_box().bottom() + bottom_shift;
+ int min_bottom, max_bottom, min_top, max_top;
+ unicharset.get_top_bottom(class_id, &min_bottom, &max_bottom,
+ &min_top, &max_top);
+ // Chars with a wild top range would mess up the result so ignore them.
+ if (max_top - min_top > kMaxCharTopRange)
+ continue;
+ int misfit_dist = std::max((min_top - x_ht_acceptance_tolerance) - top,
+ top - (max_top + x_ht_acceptance_tolerance));
+ int height = top - kBlnBaselineOffset;
+ if (debug_x_ht_level >= 2) {
+ tprintf("Class %s: height=%d, bottom=%d,%d top=%d,%d, actual=%d,%d: ",
+ unicharset.id_to_unichar(class_id),
+ height, min_bottom, max_bottom, min_top, max_top,
+ bottom, top);
+ }
+ // Use only chars that fit in the expected bottom range, and where
+ // the range of tops is sensibly near the xheight.
+ if (min_bottom <= bottom + x_ht_acceptance_tolerance &&
+ bottom - x_ht_acceptance_tolerance <= max_bottom &&
+ min_top > kBlnBaselineOffset &&
+ max_top - kBlnBaselineOffset >= kBlnXHeight &&
+ misfit_dist > 0) {
+ // Compute the x-height position using proportionality between the
+ // actual height and expected height.
+ int min_xht = DivRounded(height * kBlnXHeight,
+ max_top - kBlnBaselineOffset);
+ int max_xht = DivRounded(height * kBlnXHeight,
+ min_top - kBlnBaselineOffset);
+ if (debug_x_ht_level >= 2) {
+ tprintf(" xht range min=%d, max=%d\n", min_xht, max_xht);
+ }
+ // The range of expected heights gets a vote equal to the distance
+ // of the actual top from the expected top.
+ for (int y = min_xht; y <= max_xht; ++y)
+ top_stats.add(y, misfit_dist);
+ } else if ((min_bottom > bottom + x_ht_acceptance_tolerance ||
+ bottom - x_ht_acceptance_tolerance > max_bottom) &&
+ bottom_shift == 0) {
+ // Get the range of required bottom shift.
+ int min_shift = min_bottom - bottom;
+ int max_shift = max_bottom - bottom;
+ if (debug_x_ht_level >= 2) {
+ tprintf(" bottom shift min=%d, max=%d\n", min_shift, max_shift);
+ }
+ // The range of expected shifts gets a vote equal to the min distance
+ // of the actual bottom from the expected bottom, spread over the
+ // range of its acceptance.
+ int misfit_weight = abs(min_shift);
+ if (max_shift > min_shift)
+ misfit_weight /= max_shift - min_shift;
+ for (int y = min_shift; y <= max_shift; ++y)
+ shift_stats.add(y, misfit_weight);
+ } else {
+ if (bottom_shift == 0) {
+ // Things with bottoms that are already ok need to say so, on the
+ // 1st iteration only.
+ shift_stats.add(0, kBlnBaselineOffset);
+ }
+ if (debug_x_ht_level >= 2) {
+ tprintf(" already OK\n");
+ }
+ }
+ }
+ }
+ if (shift_stats.get_total() > top_stats.get_total()) {
+ bottom_shift = IntCastRounded(shift_stats.median());
+ if (debug_x_ht_level >= 2) {
+ tprintf("Applying bottom shift=%d\n", bottom_shift);
+ }
+ }
+ } while (bottom_shift != 0 &&
+ top_stats.get_total() < shift_stats.get_total());
+ // Baseline shift is opposite sign to the bottom shift.
+ *baseline_shift = -bottom_shift / word_res->denorm.y_scale();
+ if (debug_x_ht_level >= 2) {
+ tprintf("baseline shift=%g\n", *baseline_shift);
+ }
+ if (top_stats.get_total() == 0)
+ return bottom_shift != 0 ? word_res->x_height : 0.0f;
+ // The new xheight is just the median vote, which is then scaled out
+ // of BLN space back to pixel space to get the x-height in pixel space.
+ float new_xht = top_stats.median();
+ if (debug_x_ht_level >= 2) {
+ tprintf("Median xht=%f\n", new_xht);
+ tprintf("Mode20:A: New x-height = %f (norm), %f (orig)\n",
+ new_xht, new_xht / word_res->denorm.y_scale());
+ }
+ // The xheight must change by at least x_ht_min_change to be used.
+ if (fabs(new_xht - kBlnXHeight) >= x_ht_min_change)
+ return new_xht / word_res->denorm.y_scale();
+ else
+ return bottom_shift != 0 ? word_res->x_height : 0.0f;
+}
+
+} // namespace tesseract