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Intensity Threshold Segmenter

Allows the segments detection using one of the available automatic threshold methods.

Dialog 'Otsu Threshold - big structures' with Channel #1 (Denoising), Method Auto, Object type Bright, Thresholder Otsu

Intensity Threshold Segmenter parameters

By default, the Method: Auto is selected. Depending on the selection, different parameters are available.

Parameter

Description

Channel

Sets the processing and analysis target channel.

Method

Sets the threshold algorithm. By default, Auto is selected.

Simple

This method uses a single threshold and segments everything below or above it.

Range

This method uses two Thresholds to define the range of intensities to segment. Everything outside of this range is neglected.

Percentile

This method uses a single threshold and segments all intensities below or above it. The threshold is given as a percentile and is based on the data.

Percentile range

This method uses two thresholds to define the range of intensities to segment. Everything outside of this range is neglected. The thresholds are given as percentiles and are based on the data.

Auto

This method uses a single threshold and segments all intensities below or above it. The threshold is automatically calculated based on the data.

Adaptive mean

This method uses local information around each pixel to set a threshold in relation to the local background. It is based on Niblack's thresholding method.

Mean

This method uses local information around each pixel to set a threshold in relation to the local background.

Object type

Sets whether to select light or dark objects, i.e., whether the threshold value should be below or above.

Bright

Selects the bright objects. This is good for images with a dark background.

Dark

Selects the dark objects. This is good for images with a bright background.

Thresholder

Sets the auto algorithm to be used.

Otsu

The algorithm maximizes the inter-class variance.

Huang

The fuzzing threshold algorithm using the Shannon's entropy function.

Li

The algorithm minimizes the cross-entropy.

Yen

The algorithm is a 2-factor criterion-based automatic multilevel thresholding.

Range

Sets the extent of the input data for the automatic threshold calculation.

Plane

For each plane of the image set an individual threshold is calculated.

Time point

For each time point of the image set an individual threshold is calculated.

Image set

For the whole image set only one threshold is calculated.

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