In this space, you will find all the Segmentations in Breeze with what parameters are available and example usage

Model — Separate object from background using PCA
Model Expression — Segment objects from measurements using expressions and models.
Deep Learning image segmentation — Object detection using pre-trained algorithms via ONNX
Constrained Spectral Unmixing (segmentation) — Segmentation using unmixing of spectral data
Grid and inset — Spatial segmentation in grid format
Group (segmentation) — Separate on based on Breeze group
Horizontal interval — Spatial segmentation in the field of view width
Intensity — Segment objects from measurements using intensities in the different bands/wavelengths
Manual selection in pixel explore — Manual exploratory segmentation
Pixel class from external file — Classify objects using pixel classification from external files.
Pixel coordinates — Lets the user create a specified region in the measurement based on pixel coordinates.
Python script (segmentation) — Segmentation of measurement using an external python script.
Representative spectrum — Create sub-sample from segmentation
Shapefile — Segment the image according to the specified shapefile
Structure — Select a band at which the segmentation should be applied.