Tool Superpixel Segmentation

The Superpixel Segmentation tool implements the 'Simple Linear Iterative Clustering' (SLIC) algorithm, an image segmentation method described in Achanta et al. (2010).

SLIC is a simple and efficient method to decompose an image in visually homogeneous regions. It is based on a spatially localized version of k-means clustering. Similar to mean shift or quick shift, each pixel is associated to a feature vector.

This tool is follows the SLIC implementation created by Vedaldi and Fulkerson as part of the VLFeat library.

References

(2010): Slic Superpixels. EPFL Technical Report no. 149300, June 2010. epfl.ch.
(2012): SLIC Superpixels compared to state-of-the-art superpixel methods. IEEE transactions on pattern analysis and machine intelligence, 34(11), 2274-2282. ieee.org.
SLIC at VLFeat.org

Author: O.Conrad (c) 2019
Menu: Imagery|Segmentation

Parameters

	Name	Type	Identifier	Description	Constraints
Input	Features	Grid list (input)	`FEATURES`	-	-
Output	Segments	Shapes (output)	`POLYGONS`	-	-
Output	Superpixels (*)	Grid list (optional output)	`SUPERPIXELS`	-	-
Options	Grid system	Grid system	`PARAMETERS_GRID_SYSTEM`	-	-
	Normalize	Boolean	`NORMALIZE`	-	Default: 0
	Maximum Iterations	Integer	`MAX_ITERATIONS`	-	Minimum: 1 Default: 100
	Regularization	Floating point	`REGULARIZATION`	-	Minimum: 0.000000 Default: 1.000000
	Region Size	Integer	`SIZE`	Starting 'cell size' of the superpixels given as number of cells.	Minimum: 1 Default: 10
	Minimum Region Size	Integer	`SIZE_MIN`	In postprocessing join segments, which cover less cells than specified here, to a larger neighbour segment.	Minimum: 1 Default: 1
	Create Superpixel Grids	Boolean	`SUPERPIXELS_DO`	-	Default: 0
	Post-Processing	Choice	`POSTPROCESSING`	-	Available Choices: [0] none [1] unsupervised classification Default: 0
	Number of Clusters	Integer	`NCLUSTER`	-	Minimum: 2 Default: 12
	Split Clusters	Boolean	`SPLIT_CLUSTERS`	-	Default: 1
(*) optional

Command-line

Usage: saga_cmd imagery_segmentation 4 [-FEATURES <str>] [-NORMALIZE <str>] [-POLYGONS <str>] [-MAX_ITERATIONS <num>] [-REGULARIZATION <double>] [-SIZE <num>] [-SIZE_MIN <num>] [-SUPERPIXELS_DO <str>] [-SUPERPIXELS <str>] [-POSTPROCESSING <str>] [-NCLUSTER <num>] [-SPLIT_CLUSTERS <str>]
  -FEATURES:<str>         	Features
	Grid list (input)
  -NORMALIZE:<str>        	Normalize
	Boolean
	Default: 0
  -POLYGONS:<str>         	Segments
	Shapes (output)
  -MAX_ITERATIONS:<num>   	Maximum Iterations
	Integer
	Minimum: 1
	Default: 100
  -REGULARIZATION:<double>	Regularization
	Floating point
	Minimum: 0.000000
	Default: 1.000000
  -SIZE:<num>             	Region Size
	Integer
	Minimum: 1
	Default: 10
  -SIZE_MIN:<num>         	Minimum Region Size
	Integer
	Minimum: 1
	Default: 1
  -SUPERPIXELS_DO:<str>   	Create Superpixel Grids
	Boolean
	Default: 0
  -SUPERPIXELS:<str>      	Superpixels
	Grid list (optional output)
  -POSTPROCESSING:<str>   	Post-Processing
	Choice
	Available Choices:
	[0] none
	[1] unsupervised classification
	Default: 0
  -NCLUSTER:<num>         	Number of Clusters
	Integer
	Minimum: 2
	Default: 12
  -SPLIT_CLUSTERS:<str>   	Split Clusters
	Boolean
	Default: 1