Individual Measurements
Analysis algorithms applying a measurement on each label of the input image.
- VolumeFractionByLabel: Computes the volume fraction occupied by each object or region of a segmented image.
- LabelCountByRegion: Computes, for each region of a first label image, the number of objects contained in a second label image.
- VolumeFractionByRegion: Computes, for each region of a first label image, the intersection ratio with particles of a second label image.
- LabelAnalysis: Computes a set of measurements on objects defined in a label image.
- LabelFiltering: Removes objects from a label image based on measurement criteria.
- LabelFilteringAnalysis: Computes measurements on objects and filters them from a label image.
- FilterAnalysis: Filters objects from an analysis object.
- MeasurementToImage: Replaces all labels of the input image by the result of an individual measurement.
- FilterByMeasurement: Preserves a predefined number of objects according to a selected measurement.
- SieveLabeling: Produces a new label image by assigning a same label to objects belonging to a same class of a user-defined measurement.
For an introduction: Image Analysis
Most of these algorithms have a field to select one or several input measurements.
The following algorithms filter an image with a criterion defined in a formula:
For example, to define a filter preserving particles having a diameter lower than 50, in the coordinate system defined by the image calibration, in C#:
Most of these algorithms have a field to select one or several input measurements.
Filtering objects in an image
The object filtering algorithms remove or preserve shapes from a binary or label image according to measurement criteria.The following algorithms filter an image with a criterion defined in a formula:
For example, to define a filter preserving particles having a diameter lower than 50, in the coordinate system defined by the image calibration, in C#:
labelFilter.inputFilter = NativeMeasurements.EqDiameter.name + "< 50"