Tool Name	Object Based Image Segmentation
Tool ID	obia
Library ID	imagery_segmentation
Version	1.0
Author(s)	O.Conrad (c) 2014

Description

This Object Based Image Segmentation tool chain combines a number of tools for an easy derivation of geo-objects as polygons and is typically applied to satellite imagery. Segmentation is done using a 'Seeded Region Growing Algorithm'. Optionally the resulting polygons can be grouped by an unsupervised classification (k-means cluster analysis) or supervised classification (needs classified feature samples as additional input), both is performed on the basis of zonal feature grid statistics for each polygon object.

References

Adams, R. & Bischof, L. (1994): Seeded Region Growing. IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol.16, No.6, p.641-647.

Bechtel, B., Ringeler, A. & Boehner, J. (2008): Segmentation for Object Extraction of Trees using MATLAB and SAGA. In: Boehner, J., Blaschke, T., Montanarella, L. [Eds.]: SAGA - Seconds Out. Hamburger Beitraege zur Physischen Geographie und Landschaftsoekologie, 19:59-70. online

Parameters

Name	Type	Identifier	Description	Constraints
Input
Features	grid list, input	FEATURES
Training Samples	table, input	SAMPLES	Training samples for supervised classification. Provide a class identifier in the first field followed by sample data corresponding to the selected feature attributes
Output
Segments	shapes, output	OBJECTS
Options
Normalize	boolean	NORMALIZE		Default: 0
Vertices	choice	VERTICES		Available Choices: [0] cell corners [1] smoothed cell corners [2] cell edge centers [3] cell edge center with less smoothed cell corners [4] cell edge center with smoothed cell corners Default: 0
Band Width for Seed Point Generation	floating point number	SEEDS_BAND_WIDTH	Increase band width to get less seed points.	Default: 2.000000
Neighbourhood	choice	RGA_NEIGHBOUR		Available Choices: [0] 4 (Neumann) [1] 8 (Moore) Default: 0
Distance	choice	RGA_METHOD		Available Choices: [0] feature space and position [1] feature space Default: 0
Variance in Feature Space	floating point number	RGA_SIG_1		Minimum: 0.000000 Default: 1.000000
Variance in Position Space	floating point number	RGA_SIG_2		Minimum: 0.000000 Default: 1.000000
Similarity Threshold	floating point number	RGA_SIMILARITY		Minimum: 0.000000 Default: 0.000000
Generalization	integer number	MAJORITY_RADIUS	Applies a majority filter with given search radius to the segments grid. Is skipped if set to zero.	Default: 1
Classification	choice	CLASSIFICATION		Available Choices: [0] none [1] cluster analysis [2] supervised classification Default: 0
Split Distinct Polygon Parts	choice	SPLIT_POLYGONS		Available Choices: [0] no [1] yes Default: 0
Number of Clusters	integer number	NCLUSTER		Default: 10
Method	choice	CLASSIFIER		Available Choices: [0] Binary Encoding [1] Parallelepiped [2] Minimum Distance [3] Mahalanobis Distance [4] Maximum Likelihood [5] Spectral Angle Mapping Default: 0