Multilevel Thresholding

By now, only the Otsu method is implemented in an efficient way using lookup-tables.

Options

Thresholding method

The method to use for thresholding. Currently only OTSU is available, but more methods might be added in the future.

Parameters

Important parameters. Number of levels specifies the number of levels in the output image. Number of intensities states, how many bins are used in the input image's histogram.

Dimension Selection

This component allows the selection of dimensions of interest. If an algorithm cannot, as it only supports fewer dimensions than the number of dimensions of the image, or shouldnot, as one wants to run the algorithm only on subsets of the image, be applied on the complete image, the dimension selection can be used to define the plane/cube/hypercube on which the algorithm is applied. Example 1 with three dimensional Image (X,Y,Time): An algorithm cannot be applied to the complete image, as it only supports two dimensional images. If you select e.g. X,Y then the algorithm will be applied to all X,Y planes individually. Example 2 with three dimensional Image (X,Y,Time): The algorithm can be applied in two, three or even more dimensions. Select the dimensions to define your plane/cube/hypercube on which the algorithm will be applied.

Column Selection

Column Creation Mode

Mode how to handle the selected column. The processed column can be added to a new table, appended to the end of the table, or the old column can be replaced by the new result

Column Suffix

A suffix appended to the column name. If "Append" is not selected, it can be left empty.

Column Selection

Selection of the columns to be processed.

Views

Image Viewer

Another, possibly interactive, view on table cells. Displays the selected cells with their associated viewer if it exists. Available views are:
- Image Viewer
-- This viewer renders the selected image-cell.
- XML
-- XML tree
- Combined View
-- A viewer shown when the user selects an interval of rows and columns in the viewer. This viewer combines all images and labelings in the selected interval to one image by rendering them next to each other. Alternatively, the images and labelings can be layed over each other.
- BigDataViewer
-- A viewer shown when the user selects an interval of rows and columns in the viewer. This viewer combines all images and labelings in the selected interval to one image by rendering them next to each other. Alternatively, the images and labelings can be layed over each other.
- Labeling View
-- View on a labeling/segmentation
- Histogram Viewer
-- This viewer shows the histogram of the currently selected image.
- Missing Value Viewer
-- An empty viewer that is shown when the input cell has no value to display.

Workflows

• 02_MinimumKNIME Hub
• 20211027_Bildanalyse_V0KNIME Hub

Links

• No links available

Developers