/usr/include/ITK-4.12/itkLiThresholdCalculator.hxx is in libinsighttoolkit4-dev 4.12.2-dfsg1-1ubuntu1.
This file is owned by root:root, with mode 0o644.
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*
* Copyright Insight Software Consortium
*
* 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.txt
*
* 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.
*
*=========================================================================*/
#ifndef itkLiThresholdCalculator_hxx
#define itkLiThresholdCalculator_hxx
#include "itkLiThresholdCalculator.h"
#include "itkProgressReporter.h"
#include "itkMath.h"
namespace itk
{
template<typename THistogram, typename TOutput>
void
LiThresholdCalculator<THistogram, TOutput>
::GenerateData(void)
{
const HistogramType * histogram = this->GetInput();
if ( histogram->GetTotalFrequency() == 0 )
{
itkExceptionMacro(<< "Histogram is empty");
}
ProgressReporter progress(this, 0, histogram->GetSize(0) );
if( histogram->GetSize(0) == 1 )
{
this->GetOutput()->Set( static_cast<OutputType>( histogram->GetMeasurement(0,0) ) );
}
unsigned int size = histogram->GetSize(0);
long int histthresh;
int ih;
int num_pixels;
double sum_back; // sum of the background pixels at a given threshold
double sum_obj; // sum of the object pixels at a given threshold
int num_back; // number of background pixels at a given threshold
int num_obj; // number of object pixels at a given threshold
double old_thresh;
double new_thresh;
double mean_back; // mean of the background pixels at a given threshold
double mean_obj; // mean of the object pixels at a given threshold
double mean; // mean gray-level in the image
double tolerance; // threshold tolerance
double temp;
tolerance = 0.5;
num_pixels = histogram->GetTotalFrequency();
// Calculate the mean gray-level
mean = 0.0;
for ( ih = 0; (unsigned)ih < size; ih++ ) //0 + 1?
{
mean += histogram->GetMeasurement(ih, 0) * histogram->GetFrequency(ih, 0);
}
mean /= num_pixels;
// Initial estimate
new_thresh = mean;
do {
old_thresh = new_thresh;
typename HistogramType::MeasurementVectorType ot(1);
ot.Fill((int) (old_thresh + 0.5));
{
typename HistogramType::IndexType local_index;
histogram->GetIndex(ot, local_index);
histthresh = local_index[0];
}
// Calculate the means of background and object pixels
// Background
sum_back = 0;
num_back = 0;
for ( ih = 0; ih <= histthresh; ih++ )
{
sum_back += histogram->GetMeasurement(ih, 0) * histogram->GetFrequency(ih, 0);
num_back += histogram->GetFrequency(ih, 0);
}
mean_back = ( num_back == 0 ? 0.0 : ( sum_back / ( double ) num_back ) );
// Object
sum_obj = 0;
num_obj = 0;
for ( ih = histthresh + 1; (unsigned)ih < size; ih++ )
{
sum_obj += histogram->GetMeasurement(ih, 0) * histogram->GetFrequency(ih, 0);
num_obj += histogram->GetFrequency(ih, 0);
}
mean_obj = ( num_obj == 0 ? 0.0 : ( sum_obj / ( double ) num_obj ) );
// Calculate the new threshold: Equation (7) in Ref. 2
//new_thresh = simple_round ( ( mean_back - mean_obj ) / ( Math.log ( mean_back ) - Math.log ( mean_obj ) ) );
//simple_round ( double x ) {
// return ( int ) ( IS_NEG ( x ) ? x - .5 : x + .5 );
//}
//
//#define IS_NEG( x ) ( ( x ) < -DBL_EPSILON )
//
temp = ( mean_back - mean_obj ) / ( std::log ( mean_back ) - std::log ( mean_obj ) );
double epsilon = itk::NumericTraits<double>::epsilon();
if( temp < -epsilon )
{
new_thresh = (int) (temp - 0.5);
}
else
{
new_thresh = (int) (temp + 0.5);
}
// Stop the iterations when the difference between the new and old threshold
// values is less than the tolerance
}
while ( std::abs ( new_thresh - old_thresh ) > tolerance );
this->GetOutput()->Set( static_cast<OutputType>( histogram->GetMeasurement( histthresh, 0 ) ) );
}
} // end namespace itk
#endif
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