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Section Navigation

  • Feature Detection
    • Threshold Feature Detection Parameters
    • Feature Detection Output
    • How multiple thresholds changes the features detected
    • How n_min_threshold changes what features are detected
    • Different threshold_position options
    • tobac Feature Detection Filtering
  • Segmentation
    • Watershedding Segmentation Parameters
    • Segmentation Output
    • Features without segmented areas
    • Track on one dataset, segment on another
  • Tracking
    • Tracking Output
  • Compute bulk statistics
    • tobac example: Compute bulk statistics during feature detection
    • tobac example: Compute bulk statistics during segmentation
    • tobac example: Compute bulk statistics as a postprocessing step
  • Handling Large Datasets
  • Analysis
  • Refereed Publications Using tobac
  • Governance
  • User Guide
  • Segmentation

Segmentation#

Segmentation allows you to expand from the individual points of feature detection to grids of data. These pages serve to go more in depth on segmentation parameters and options and the implications of using each of them.

  • Watershedding Segmentation Parameters
    • Basic Operating Procedure
    • Target
    • Threshold
    • Projecting 2D Spatial Features into 3D Segmentation
    • Projecting 3D Spatial Features into 2D Segmentation
    • Projecting 3D Spatial Features into 3D Segmentation
    • Maximum Distance
  • Segmentation Output
  • Features without segmented areas
    • Case 1: Segmentation threshold
    • Case 2: Feature position
  • Track on one dataset, segment on another

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