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Madagascar2011 - 08 - OTB segmentation and classification
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Madagascar2011 - 08 - OTB segmentation and classification

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  • 1. Orfeo ToolboxSegmentation, classification Stéphane MAY stephane.may@cnes.fr orfeo-toolbox.org 1
  • 2. SegmentationDefinition of segmentation Extract the outlines of different regions in the image Divide the image the image into regions with pixels which have something in commonOTB – Monteverdi Meanshift segmentation moduleOTB (integration of ITK library) Watershed segmentation Region growing segmentation Level set segmentation Hybrid segmentation, etc... orfeo-toolbox.org 2
  • 3. Monteverdi – Mean-shiftFiltering > Meanshift clustering orfeo-toolbox.org 3
  • 4. Use case 1 : segmentation with mean-shiftMenu File > Open ./theme2/extraitIm2_C/Im2_c_extrait.tifMenu Filtering > Mean-shift clustering Change radius : 5 Spectral radius : 15 Min region size : 15 Clusters : ON Change values and Click on Run button Click on Close button after selecting right set of parameters See also : ➢ Image filtered / Image clustered ➢ See OTB-Software-Guide.pdf for details orfeo-toolbox.org 4
  • 5. Orfeo toolbox - otbSegmentationApplicationotbSegmentationApplication orfeo-toolbox.org 5
  • 6. otbSegmentationApplication (1/8) orfeo-toolbox.org 6
  • 7. otbSegmentationApplication (2/8) orfeo-toolbox.org 7
  • 8. otbSegmentationApplication (3/8) orfeo-toolbox.org 8
  • 9. otbSegmentationApplication (4/8) orfeo-toolbox.org 9
  • 10. otbSegmentationApplication (5/8) orfeo-toolbox.org 10
  • 11. otbSegmentationApplication (6/8) orfeo-toolbox.org 11
  • 12. otbSegmentationApplication (7/8) orfeo-toolbox.org 12
  • 13. otbSegmentationApplication (8/8) orfeo-toolbox.org 13
  • 14. Use case 2 : otbSegmentationApplicationCommand line application : otbSegmentationApplication Open ./theme2/extraitIm2_C/Im2_c_extrait.tif Segment homogeneous areas Save your results orfeo-toolbox.org 14
  • 15. Monteverdi – Classification modulesMenu Learning SVM classification K-Means clustering orfeo-toolbox.org 15
  • 16. MonteverdiMenu Learning > K-means orfeo-toolbox.org 16
  • 17. Use case 3 : unsupervised clustering with k-meansMenu File > Open ./theme2/extraitIm2_C/Im2_c_extrait.tifMenu Learning > k-means clustering (doc OTBSoftwareGuide.pdf) Training 15% Number of classes : 5 Iteration number : 100 Convergence : 0.0001Save your resultsTry with several parameters setVisualization > Viewer > Compare results orfeo-toolbox.org 17
  • 18. MonteverdiMenu Learning > SVM classification (1/3) orfeo-toolbox.org 18
  • 19. MonteverdiMenu Learning > SVM classification (2/3) orfeo-toolbox.org 19
  • 20. MonteverdiMenu Learning > SVM classification (3/3) orfeo-toolbox.org 20
  • 21. Use case 4 : supervised classification with SVM (1/2) Menu File > Open ./theme2/IM2/extraitIm2_C/Im2_c_extrait.tif Menu Learning > SVM Classification Create several classes (4-5) ➢ Add ➢ Select polygons (right click to end a polygon) ➢ Edit names ➢ Change colors Learn Display orfeo-toolbox.org 21
  • 22. Use case 4 : supervised classification with SVM (2/2) Menu Learning > SVM Classification Deselect random validation set Select Display validation Select your classes 1 by 1 ➢ Select polygons (right click to end a polygon) Display Validate File > Export selected polygons orfeo-toolbox.org 22
  • 23. Monteverdi – Feature extractionFiltering Feature Extraction (1/4) orfeo-toolbox.org 23
  • 24. Monteverdi – Feature extractionFiltering Feature Extraction (2/4) orfeo-toolbox.org 24
  • 25. Monteverdi – Feature extractionMenu Filtering > Feature Extraction (3/4) Mean, variance, Gradient, spectral angle Original data (=> no need to concatenate channels after filtering) Textures (energy, entropy, contrast, etc) Morphological filters Radiometric indexes Vegetation (NDVI, ARVI, etc), Soil, Built up, Water Edge density Mean shift orfeo-toolbox.org 25
  • 26. Monteverdi – Feature extractionMenu Filtering > Feature extraction (4/4) Radiometric indexes ➢ Vegetation NDVI, RVI, PVI, etc ➢ Soil BI2 ➢ Built up ISU orfeo-toolbox.org 26
  • 27. Use case 5 : Segment with Feature extractionMenu File > Open ./theme2/IM2/extraitIm2_C/Im2_c_extrait.tifMenu Filtering > Feature extraction Test the following features (See OTB-Software-Guide.pdf for technical details on algorithms) ➢ Original data (=> no need to concatenate channels after filtering) ➢ Spectral angle : choose one vegetation pixel ➢ Variance, mean ➢ NDVI ➢ Meanshift filtering, etc.Menu Learning > K-MeansMenu Learning > SVM (import polygons)Compare your results orfeo-toolbox.org 27
  • 28. MonteverdiThank you for your attention ! orfeo-toolbox.org 28

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