Segmentations

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

Constrained Spectral Unmixing (segmentation) — Segmentation using unmixing of spectral data

Deep Learning segmentation — Object detection using pre-trained algorithms via ONNX models

Depth interval registration (segmentation) — Set incremental segmentation based on the depth registration

Depth registration (segmentation) — Segment on registered core areas / depth

Frames (segmentation) — Split data into different measurements based on the number of frames.

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 (segmentation) — Manual exploratory segmentation

Model — Separate object from background using PCA

Model Expression — Segment objects from measurements using expressions and models.

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 — Identify objects by utilizing the spatial structure differences at the specified band

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