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https://github.com/tesseract-ocr/tesseract.git
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08defee46e
git-svn-id: https://tesseract-ocr.googlecode.com/svn/trunk@450 d0cd1f9f-072b-0410-8dd7-cf729c803f20
380 lines
12 KiB
C++
380 lines
12 KiB
C++
/******************************************************************************
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** Filename: MergeNF.c
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** Purpose: Program for merging similar nano-feature protos
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** Author: Dan Johnson
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** History: Wed Nov 21 09:55:23 1990, DSJ, Created.
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**
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** (c) Copyright Hewlett-Packard Company, 1988.
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** Licensed under the Apache License, Version 2.0 (the "License");
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** you may not use this file except in compliance with the License.
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** You may obtain a copy of the License at
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** http://www.apache.org/licenses/LICENSE-2.0
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** Unless required by applicable law or agreed to in writing, software
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** distributed under the License is distributed on an "AS IS" BASIS,
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** WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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** See the License for the specific language governing permissions and
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** limitations under the License.
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******************************************************************************/
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/*----------------------------------------------------------------------------
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Include Files and Type Defines
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-----------------------------------------------------------------------------*/
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#include "mergenf.h"
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#include "general.h"
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#include "efio.h"
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#include "clusttool.h"
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#include "cluster.h"
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#include "oldlist.h"
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#include "protos.h"
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#include "ndminx.h"
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#include "ocrfeatures.h"
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#include "const.h"
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#include "featdefs.h"
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#include "intproto.h"
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#include "varable.h"
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#include <stdio.h>
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#include <string.h>
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#include <math.h>
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/*----------------------------------------------------------------------------
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Variables
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-----------------------------------------------------------------------------*/
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/*-------------------once in subfeat---------------------------------*/
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double_VAR(training_angle_match_scale, 1.0, "Angle Match Scale ...");
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double_VAR(training_similarity_midpoint, 0.0075, "Similarity Midpoint ...");
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double_VAR(training_similarity_curl, 2.0, "Similarity Curl ...");
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/*-----------------------------once in fasttrain----------------------------------*/
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double_VAR(training_tangent_bbox_pad, 0.5, "Tangent bounding box pad ...");
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double_VAR(training_orthogonal_bbox_pad, 2.5, "Orthogonal bounding box pad ...");
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double_VAR(training_angle_pad, 45.0, "Angle pad ...");
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/*----------------------------------------------------------------------------
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Global Data Definitions and Declarations
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----------------------------------------------------------------------------*/
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//int row_number; /* kludge due to linking problems */
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/*----------------------------------------------------------------------------
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Public Code
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----------------------------------------------------------------------------*/
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/*---------------------------------------------------------------------------*/
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/**
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* Compare protos p1 and p2 and return an estimate of the
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* worst evidence rating that will result for any part of p1
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* that is compared to p2. In other words, if p1 were broken
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* into pico-features and each pico-feature was matched to p2,
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* what is the worst evidence rating that will be achieved for
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* any pico-feature.
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*
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* @param p1, p2 protos to be compared
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*
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* Globals: none
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*
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* @return Worst possible result when matching p1 to p2.
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* @note Exceptions: none
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* @note History: Mon Nov 26 08:27:53 1990, DSJ, Created.
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*/
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FLOAT32 CompareProtos(PROTO p1, PROTO p2) {
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FEATURE Feature;
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FLOAT32 WorstEvidence = WORST_EVIDENCE;
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FLOAT32 Evidence;
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FLOAT32 Angle, Length;
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/* if p1 and p2 are not close in length, don't let them match */
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Length = fabs (p1->Length - p2->Length);
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if (Length > MAX_LENGTH_MISMATCH)
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return (0.0);
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/* create a dummy pico-feature to be used for comparisons */
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Feature = NewFeature (&PicoFeatDesc);
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Feature->Params[PicoFeatDir] = p1->Angle;
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/* convert angle to radians */
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Angle = p1->Angle * 2.0 * PI;
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/* find distance from center of p1 to 1/2 picofeat from end */
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Length = p1->Length / 2.0 - GetPicoFeatureLength () / 2.0;
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if (Length < 0) Length = 0;
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/* set the dummy pico-feature at one end of p1 and match it to p2 */
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Feature->Params[PicoFeatX] = p1->X + cos (Angle) * Length;
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Feature->Params[PicoFeatY] = p1->Y + sin (Angle) * Length;
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if (DummyFastMatch (Feature, p2)) {
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Evidence = SubfeatureEvidence (Feature, p2);
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if (Evidence < WorstEvidence)
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WorstEvidence = Evidence;
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} else {
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FreeFeature(Feature);
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return 0.0;
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}
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/* set the dummy pico-feature at the other end of p1 and match it to p2 */
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Feature->Params[PicoFeatX] = p1->X - cos (Angle) * Length;
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Feature->Params[PicoFeatY] = p1->Y - sin (Angle) * Length;
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if (DummyFastMatch (Feature, p2)) {
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Evidence = SubfeatureEvidence (Feature, p2);
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if (Evidence < WorstEvidence)
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WorstEvidence = Evidence;
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} else {
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FreeFeature(Feature);
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return 0.0;
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}
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FreeFeature (Feature);
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return (WorstEvidence);
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} /* CompareProtos */
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/*---------------------------------------------------------------------------*/
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/**
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* This routine computes a proto which is the weighted
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* average of protos p1 and p2. The new proto is returned
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* in MergedProto.
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*
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* @param p1, p2 protos to be merged
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* @param w1, w2 weight of each proto
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* @param MergedProto place to put resulting merged proto
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*
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* Globals: none
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*
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* @return none (results are returned in MergedProto)
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* @note Exceptions: none
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* @note History: Mon Nov 26 08:15:08 1990, DSJ, Created.
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*/
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void ComputeMergedProto (PROTO p1,
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PROTO p2,
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FLOAT32 w1,
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FLOAT32 w2,
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PROTO MergedProto)
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{
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FLOAT32 TotalWeight;
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TotalWeight = w1 + w2;
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w1 /= TotalWeight;
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w2 /= TotalWeight;
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MergedProto->X = p1->X * w1 + p2->X * w2;
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MergedProto->Y = p1->Y * w1 + p2->Y * w2;
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MergedProto->Length = p1->Length * w1 + p2->Length * w2;
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MergedProto->Angle = p1->Angle * w1 + p2->Angle * w2;
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FillABC(MergedProto);
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} /* ComputeMergedProto */
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/*---------------------------------------------------------------------------*/
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/**
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* This routine searches thru all of the prototypes in
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* Class and returns the id of the proto which would provide
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* the best approximation of Prototype. If no close
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* approximation can be found, NO_PROTO is returned.
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*
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* @param Class class to search for matching old proto in
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* @param NumMerged # of protos merged into each proto of Class
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* @param Prototype new proto to find match for
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*
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* Globals: none
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*
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* @return Id of closest proto in Class or NO_PROTO.
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* @note Exceptions: none
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* @note History: Sat Nov 24 11:42:58 1990, DSJ, Created.
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*/
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int FindClosestExistingProto(CLASS_TYPE Class, int NumMerged[],
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PROTOTYPE *Prototype) {
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PROTO_STRUCT NewProto;
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PROTO_STRUCT MergedProto;
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int Pid;
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PROTO Proto;
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int BestProto;
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FLOAT32 BestMatch;
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FLOAT32 Match, OldMatch, NewMatch;
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MakeNewFromOld (&NewProto, Prototype);
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BestProto = NO_PROTO;
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BestMatch = WORST_MATCH_ALLOWED;
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for (Pid = 0; Pid < Class->NumProtos; Pid++) {
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Proto = ProtoIn(Class, Pid);
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ComputeMergedProto(Proto, &NewProto,
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(FLOAT32) NumMerged[Pid], 1.0, &MergedProto);
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OldMatch = CompareProtos(Proto, &MergedProto);
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NewMatch = CompareProtos(&NewProto, &MergedProto);
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Match = MIN(OldMatch, NewMatch);
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if (Match > BestMatch) {
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BestProto = Pid;
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BestMatch = Match;
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}
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}
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return BestProto;
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} /* FindClosestExistingProto */
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/*---------------------------------------------------------------------------*/
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/**
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* This fills in the fields of the New proto based on the
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* fields of the Old proto.
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*
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* @param New new proto to be filled in
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* @param Old old proto to be converted
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*
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* Globals: none
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*
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* Exceptions: none
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* History: Mon Nov 26 09:45:39 1990, DSJ, Created.
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*/
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void MakeNewFromOld(PROTO New, PROTOTYPE *Old) {
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New->X = CenterX(Old->Mean);
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New->Y = CenterY(Old->Mean);
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New->Length = LengthOf(Old->Mean);
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New->Angle = OrientationOf(Old->Mean);
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FillABC(New);
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} /* MakeNewFromOld */
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/*-------------------once in subfeat---------------------------------*/
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/**
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* @name SubfeatureEvidence
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*
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* Compare a feature to a prototype. Print the result.
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*/
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FLOAT32 SubfeatureEvidence(FEATURE Feature, PROTO Proto) {
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float Distance;
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float Dangle;
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Dangle = Proto->Angle - Feature->Params[PicoFeatDir];
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if (Dangle < -0.5) Dangle += 1.0;
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if (Dangle > 0.5) Dangle -= 1.0;
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Dangle *= training_angle_match_scale;
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Distance = Proto->A * Feature->Params[PicoFeatX] +
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Proto->B * Feature->Params[PicoFeatY] +
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Proto->C;
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return (EvidenceOf (Distance * Distance + Dangle * Dangle));
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}
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/**
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* @name EvidenceOf
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*
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* Return the new type of evidence number corresponding to this
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* distance value. This number is no longer based on the chi squared
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* approximation. The equation that represents the transform is:
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* 1 / (1 + (sim / midpoint) ^ curl)
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*/
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FLOAT32 EvidenceOf (
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register FLOAT32 Similarity)
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{
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Similarity /= training_similarity_midpoint;
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if (training_similarity_curl == 3)
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Similarity = Similarity * Similarity * Similarity;
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else if (training_similarity_curl == 2)
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Similarity = Similarity * Similarity;
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else
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Similarity = static_cast<float>(pow(static_cast<double>(Similarity),
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training_similarity_curl));
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return (1.0 / (1.0 + Similarity));
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}
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/*---------------------------------------------------------------------------*/
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/**
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* This routine returns TRUE if Feature would be matched
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* by a fast match table built from Proto.
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*
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* @param Feature feature to be "fast matched" to proto
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* @param Proto proto being "fast matched" against
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*
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* Globals:
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* - training_tangent_bbox_pad bounding box pad tangent to proto
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* - training_orthogonal_bbox_pad bounding box pad orthogonal to proto
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*
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* @return TRUE if feature could match Proto.
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* @note Exceptions: none
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* @note History: Wed Nov 14 17:19:58 1990, DSJ, Created.
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*/
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BOOL8 DummyFastMatch (
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FEATURE Feature,
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PROTO Proto)
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{
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FRECT BoundingBox;
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FLOAT32 MaxAngleError;
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FLOAT32 AngleError;
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MaxAngleError = training_angle_pad / 360.0;
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AngleError = fabs (Proto->Angle - Feature->Params[PicoFeatDir]);
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if (AngleError > 0.5)
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AngleError = 1.0 - AngleError;
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if (AngleError > MaxAngleError)
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return (FALSE);
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ComputePaddedBoundingBox (Proto,
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training_tangent_bbox_pad * GetPicoFeatureLength (),
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training_orthogonal_bbox_pad * GetPicoFeatureLength (),
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&BoundingBox);
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return PointInside(&BoundingBox, Feature->Params[PicoFeatX],
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Feature->Params[PicoFeatY]);
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} /* DummyFastMatch */
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/*----------------------------------------------------------------------------*/
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/**
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* This routine computes a bounding box that encloses the
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* specified proto along with some padding. The
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* amount of padding is specified as separate distances
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* in the tangential and orthogonal directions.
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*
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* @param Proto proto to compute bounding box for
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* @param TangentPad amount of pad to add in direction of segment
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* @param OrthogonalPad amount of pad to add orthogonal to segment
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* @param[out] BoundingBox place to put results
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*
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* Globals: none
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*
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* @return none (results are returned in BoundingBox)
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* @note Exceptions: none
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* @note History: Wed Nov 14 14:55:30 1990, DSJ, Created.
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*/
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void ComputePaddedBoundingBox (PROTO Proto, FLOAT32 TangentPad,
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FLOAT32 OrthogonalPad, FRECT *BoundingBox) {
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FLOAT32 Pad, Length, Angle;
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FLOAT32 CosOfAngle, SinOfAngle;
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Length = Proto->Length / 2.0 + TangentPad;
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Angle = Proto->Angle * 2.0 * PI;
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CosOfAngle = fabs(cos(Angle));
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SinOfAngle = fabs(sin(Angle));
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Pad = MAX (CosOfAngle * Length, SinOfAngle * OrthogonalPad);
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BoundingBox->MinX = Proto->X - Pad;
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BoundingBox->MaxX = Proto->X + Pad;
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Pad = MAX(SinOfAngle * Length, CosOfAngle * OrthogonalPad);
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BoundingBox->MinY = Proto->Y - Pad;
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BoundingBox->MaxY = Proto->Y + Pad;
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} /* ComputePaddedBoundingBox */
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/*--------------------------------------------------------------------------*/
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/**
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* Return TRUE if point (X,Y) is inside of Rectangle.
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*
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* Globals: none
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*
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* @return TRUE if point (X,Y) is inside of Rectangle.
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* @note Exceptions: none
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* @note History: Wed Nov 14 17:26:35 1990, DSJ, Created.
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*/
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BOOL8 PointInside(FRECT *Rectangle, FLOAT32 X, FLOAT32 Y) {
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if (X < Rectangle->MinX) return (FALSE);
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if (X > Rectangle->MaxX) return (FALSE);
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if (Y < Rectangle->MinY) return (FALSE);
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if (Y > Rectangle->MaxY) return (FALSE);
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return (TRUE);
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} /* PointInside */
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