1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
|
/*=========================================================================
*
* Copyright NumFOCUS
*
* 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
*
* https://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 itkZeroCrossingBasedEdgeDetectionImageFilter_hxx
#define itkZeroCrossingBasedEdgeDetectionImageFilter_hxx
#include "itkDiscreteGaussianImageFilter.h"
#include "itkLaplacianImageFilter.h"
#include "itkZeroCrossingImageFilter.h"
#include "itkProgressAccumulator.h"
namespace itk
{
template <typename TInputImage, typename TOutputImage>
ZeroCrossingBasedEdgeDetectionImageFilter<TInputImage, TOutputImage>::ZeroCrossingBasedEdgeDetectionImageFilter()
{
m_Variance.Fill(1.0);
m_MaximumError.Fill(0.01);
m_BackgroundValue = OutputImagePixelType{};
m_ForegroundValue = NumericTraits<OutputImagePixelType>::OneValue();
}
template <typename TInputImage, typename TOutputImage>
void
ZeroCrossingBasedEdgeDetectionImageFilter<TInputImage, TOutputImage>::GenerateData()
{
typename InputImageType::ConstPointer input = this->GetInput();
// Create the filters that are needed
typename DiscreteGaussianImageFilter<TInputImage, TOutputImage>::Pointer gaussianFilter =
DiscreteGaussianImageFilter<TInputImage, TOutputImage>::New();
typename LaplacianImageFilter<TInputImage, TOutputImage>::Pointer laplacianFilter =
LaplacianImageFilter<TInputImage, TOutputImage>::New();
typename ZeroCrossingImageFilter<TInputImage, TOutputImage>::Pointer zerocrossingFilter =
ZeroCrossingImageFilter<TInputImage, TOutputImage>::New();
// Create a process accumulator for tracking the progress of this minipipeline
auto progress = ProgressAccumulator::New();
progress->SetMiniPipelineFilter(this);
// Construct the mini-pipeline
// Apply the Gaussian filter
gaussianFilter->SetVariance(m_Variance);
gaussianFilter->SetMaximumError(m_MaximumError);
gaussianFilter->SetInput(input);
progress->RegisterInternalFilter(gaussianFilter, 1.0f / 3.0f);
// Calculate the laplacian of the smoothed image
laplacianFilter->SetInput(gaussianFilter->GetOutput());
progress->RegisterInternalFilter(laplacianFilter, 1.0f / 3.0f);
// Find the zero-crossings of the laplacian
zerocrossingFilter->SetInput(laplacianFilter->GetOutput());
zerocrossingFilter->SetBackgroundValue(m_BackgroundValue);
zerocrossingFilter->SetForegroundValue(m_ForegroundValue);
zerocrossingFilter->GraftOutput(this->GetOutput());
progress->RegisterInternalFilter(zerocrossingFilter, 1.0f / 3.0f);
zerocrossingFilter->Update();
// Graft the output of the mini-pipeline back onto the filter's output.
// This action copies back the region ivars and meta-data
this->GraftOutput(zerocrossingFilter->GetOutput());
}
template <typename TInputImage, typename TOutputImage>
void
ZeroCrossingBasedEdgeDetectionImageFilter<TInputImage, TOutputImage>::PrintSelf(std::ostream & os, Indent indent) const
{
Superclass::PrintSelf(os, indent);
os << indent << "Variance: " << m_Variance << std::endl;
os << indent << "MaximumError: " << m_MaximumError << std::endl;
os << indent
<< "ForegroundValue: " << static_cast<typename NumericTraits<OutputImagePixelType>::PrintType>(m_ForegroundValue)
<< std::endl;
os << indent
<< "BackgroundValue: " << static_cast<typename NumericTraits<OutputImagePixelType>::PrintType>(m_BackgroundValue)
<< std::endl;
}
} // namespace itk
#endif
|
