4. Motivation II: Difficult examples

5. Concept

7. Segmentation I: Structure-emphasizing LBP filter Timo Ojala et al., „ Multiresolution Gray-Scale and Rotation Invariant Texture Classification with Local Binary Patterns”, IEEE Transactions on Pattern Analysis and Machine Intelligence , vol. 24, no. 7, July 2002. Rotation invariant uniform LBPs: Texture primitives: Local Binary Pattern:

8. Segmentation II: Structure-emphasizing LBP filter Rotation invariant variance measure: Rotation invariant uniform LBPs (texture primitives): For each pixel position (x,y) , fixed P , and varying R :

9. Segmentation III: Rotation compensation with HOG A. Korn, „Toward a Symbolic Representation of Intensity Changes in Images“, IEEE Transactions on Pattern Analysis and Machine Intelligence , vol. 10, no. 5, 1988.

10. Segmentation IV: Rotation compensation with HOG+PCA PCA FUSION

11. Segmentation V: Size estimation with row/col. histograms

13. Segmentation VII: Orientation and size estimation results method rotation estimation error median mean LBP & HOG & PCA with median filter 5.24° 11.65° LBP & HOG & PCA without median filter 5.99° 12.16° LBP & HOG 6.71° 12.99° LBP & PCA 12.09° 24.38° HOG only 10.68° 23.36°

14. Segmentation VIII: Examples

15. Classification I: Classes clutter (ambiguity) unstructured ship clutter ship structure 2 ship structure 1 non-ship

18. Classification IV: Examples non-ship unstructured ship unstructured ship unstructured ship clutter ship structure 1

19. Classification V: Examples for whole processing chain ship structure 2 ship structure 2 unstructured ship

21. Fraunhofer Institute of Optronics, System Technologies and Image Exploitation IOSB Karlsruhe Ettlingen Ilmenau Thanks a lot for your attention!

22. Segmentation: Orientation estimation error distrib.

23. Segmentation: Examples – The bad guys