MantisBT - ITK | |||||
View Issue Details | |||||
ID | Project | Category | View Status | Date Submitted | Last Update |
0004893 | ITK | public | 2007-04-17 07:21 | 2007-09-10 12:33 | |
Reporter | Ralf Floca | ||||
Assigned To | Luis Ibanez | ||||
Priority | low | Severity | feature | Reproducibility | always |
Status | closed | Resolution | fixed | ||
Platform | OS | OS Version | |||
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Target Version | Fixed in Version | ||||
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Summary | 0004893: itk::RegularStepGradientDescentBaseOptimizer doesn't check validity of m_GradientMagnitudeTolerance | ||||
Description | The itk::RegularStepGradientDescentBaseOptimizer doesn't check validity of the member m_GradientMagnitudeTolerance before starting the optimization. If an invalid (negative) tolerance is set, it is possible that the optimizer will have a gradientMagnitude of 0.0 but won’t stop. This causes the itk::RegularStepGradientDescentOptimizer to compute a factor of -1.#INF in itk::RegularStepGradientDescentOptimizer::AdvanceOneStep and therefore undefined transformation parameters as a step result. This causes e.g. an application to crash when the resulting transformation is used by a metric (like in image registration), because transformed points are undefined too (see also Bug 0004892). I would suggest that itk::RegularStepGradientDescentBaseOptimizer implements a validity check in itk::RegularStepGradientDescentBaseOptimizer::StartOptimization() like: if( m_GradientMagnitudeTolerance < 0.0 ) { itkExceptionMacro(<< "Gradient magnitude tolerance must be greater or equal 0.0. Current value is " << m_GradientMagnitudeTolerance ); | ||||
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Tags | No tags attached. | ||||
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Issue History | |||||
Date Modified | Username | Field | Change | ||
2007-09-10 12:23 | Luis Ibanez | Note Added: 0008906 | |||
2007-09-10 12:32 | Luis Ibanez | Note Added: 0008907 | |||
2007-09-10 12:33 | Luis Ibanez | Status | assigned => closed | ||
2007-09-10 12:33 | Luis Ibanez | Note Added: 0008908 | |||
2007-09-10 12:33 | Luis Ibanez | Resolution | open => fixed |
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