float CHAR_SAMPLE::match_sample( // Update match scores
CHAR_SAMPLE *test_sample,
BOOL8 updating) {
float score1;
float score2;
IMAGE *image = test_sample->image ();
if (sample_blob != NULL && test_sample->blob () != NULL) {
PBLOB *blob = test_sample->blob ();
DENORM *denorm = test_sample->denorm ();
score1 = compare_bln_blobs (sample_blob, sample_denorm, blob, denorm);
score2 = compare_bln_blobs (blob, denorm, sample_blob, sample_denorm);
score1 = (score1 > score2) ? score1 : score2;
}
else if (sample_image != NULL && image != NULL) {
CHAR_PROTO *sample = new CHAR_PROTO (this);
score1 = matrix_match (sample_image, image);
delete sample;
}
else
return BAD_SCORE;
if ((tessedit_use_best_sample || tessedit_cluster_debug) && updating) {
n_samples_matched++;
total_match_scores += score1;
sumsq_match_scores += score1 * score1;
}
return score1;
}
float Tesseract::compare_blobs( //match 2 blobs
PBLOB *blob1, //first blob
ROW *row1, //row it came from
PBLOB *blob2, //other blob
ROW *row2) {
PBLOB *bn_blob1; //baseline norm
PBLOB *bn_blob2;
DENORM denorm1, denorm2;
float rating; //match result
bn_blob1 = blob1->baseline_normalise (row1, &denorm1);
bn_blob2 = blob2->baseline_normalise (row2, &denorm2);
rating = compare_bln_blobs (bn_blob1, &denorm1, bn_blob2, &denorm2);
delete bn_blob1;
delete bn_blob2;
return rating;
}
