Exact Large-Scale Mean-Shift segmentation, step 4¶

Fourth step of the exact Large-Scale Mean-Shift segmentation workflow.

Detailed description¶

This application performs the fourth step of the exact Large-Scale Mean-Shift segmentation workflow (LSMS). Given a segmentation result (label image), that may have been processed for small regions merging or not, it will convert it to a GIS vector file containing one polygon per segment. Each polygon contains additional fields: mean and variance of each channels from input image (in parameter), segmentation image label, number of pixels in the polygon. For large images one can use the nbtilesx and nbtilesy parameters for tile-wise processing, with the guarantees of identical results.

Parameters¶

This section describes in details the parameters available for this application. Table [1] presents a summary of these parameters and the parameters keys to be used in command-line and programming languages. Application key is LSMSVectorization .

[1]	Table: Parameters table for Exact Large-Scale Mean-Shift segmentation, step 4.

Parameter Key	Parameter Type	Parameter Description
in	Input image	Input image
inseg	Input image	Input image
out	Output File name	Output File name
tilesizex	Int	Int
tilesizey	Int	Int
inxml	XML input parameters file	XML input parameters file
outxml	XML output parameters file	XML output parameters file

Input Image: The input image.
Segmented image: The segmented image input. Segmented image input is the segmentation of the input image.
Output GIS vector file: The output GIS vector file, representing the vectorized version of the segmented image where the features of the polygons are the radiometric means and variances.
Size of tiles in pixel (X-axis): Size of tiles along the X-axis.
Size of tiles in pixel (Y-axis): Size of tiles along the Y-axis.
Load otb application from xml file: Load otb application from xml file.
Save otb application to xml file: Save otb application to xml file.

Example¶

To run this example in command-line, use the following:

otbcli_LSMSVectorization -in avions.tif -inseg merged.tif -out vector.shp -tilesizex 256 -tilesizey 256

To run this example from Python, use the following code snippet:

#!/usr/bin/python

# Import the otb applications package
import otbApplication

# The following line creates an instance of the LSMSVectorization application
LSMSVectorization = otbApplication.Registry.CreateApplication("LSMSVectorization")

# The following lines set all the application parameters:
LSMSVectorization.SetParameterString("in", "avions.tif")

LSMSVectorization.SetParameterString("inseg", "merged.tif")

LSMSVectorization.SetParameterString("out", "vector.shp")

LSMSVectorization.SetParameterInt("tilesizex", 256)

LSMSVectorization.SetParameterInt("tilesizey", 256)

# The following line execute the application
LSMSVectorization.ExecuteAndWriteOutput()

Limitations¶

This application is part of the Large-Scale Mean-Shift segmentation workflow (LSMS) and may not be suited for any other purpose.

Authors¶

This application has been written by David Youssefi.