Tool Name	Seeded Region Growing
Tool ID	3
Library ID	imagery_segmentation
Version	1.0
Author(s)	B. Bechtel, O. Conrad (c) 2008

Description

The tool allows one to apply a seeded region growing algorithm to a stack of input features and thus to segmentize the data for object extraction. The required seed points can be created with the 'Seed Generation' tool, for example. The derived segments can be used, for example, for object based classification.

References

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

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
Seeds	grid, input	SEEDS
Features	grid list, input	FEATURES
Output
Segments	grid, output	SEGMENTS
Similarity	grid, output	SIMILARITY
Seeds	table, output	TABLE
Options
Normalize Features	boolean	NORMALIZE	Standardize the input features, i.e. rescale the input data (features) such that the mean equals 0 and the standard deviation equals 1. This is helpful when the input features have different scales, units or outliers.	Default: 0
Neighbourhood	choice	NEIGHBOUR		Available Choices: [0] 4 (von Neumann) [1] 8 (Moore) Default: 0
Method	choice	METHOD		Available Choices: [0] feature space and position [1] feature space Default: 0
Variance in Feature Space	floating point number	SIG_1		Minimum: 0.000000 Default: 1.000000
Variance in Position Space	floating point number	SIG_2		Minimum: 0.000000 Default: 1.000000
Similarity Threshold	floating point number	THRESHOLD		Minimum: 0.000000 Default: 0.000000
Refresh	boolean	REFRESH		Default: 0
Leaf Size (for Speed Optimisation)	integer number	LEAFSIZE		Minimum: 2 Default: 256