Digital Image Processing Study Group Meeting Summary

1. ICSM Group meeting Hang Xiao Oct 18, 2012

2. ICSM Organization • Regular Study • Content: Books, tools … • Each person is responsible for one chapter • How many presenter each time ? • Paper Presentation • Paper you are interested • Implemented algorithm • One main presenter • At least one paper each week • Hackathon • Interesting algorithms • Realize complex system together • C/C++, matlab, … • Questions • Need one more meeting each week? • Extend the group? Conflict with machine learning group. • Larger meeting room

3. Regular Study Books Tools ITK OpenCV • 《Digital Image Processing》 • 《Machine Vision Theory, Algorithms, Practicalities》

4. Paper PresentationJournals Image processing journals • Nature biotechnology, 23.3 • Nature method, 19.276 • PLOS Computational Biology, 5.515 • Bioinformatics, 5.468 • BMC Bioinformatics, 2.75 • IEEE transactions on pattern analysis and machine intelligence (PAMI), 4.908 • International Journal of Computer Vision， 3.741 • IEEE transactions on image processing, 3.042 • IEEE transactions on medical imaging, 3.643 • IEEE transactions on signal processing, 2.628 • Image and vision computing, 1.743 • Signal processing, 1.567 • Computerized medical imaging and graphics, 1.467 • IEEE signal processing letters, 1.388 • Journal of electronic imaging, 0.694

5. Paper PresentationJournals Machine learning journals • Pattern Recognition, 3.172 • Journal of Machine Learning Research, 2.682 • Data Mining and Knowledge Discovery, 1.545 • …

6. Paper PresentationConferences • CVPR: IEEE Computer Vision and Pattern Recognition • ICIP : IEEE Internal Conference on Image Processing • ICASSP: • ICCV: International Conference on Computer Vision • ACCV: Asian Conference on Computer Vision

7. Digital Image Processing • 1236 - xiaoyong • Frequency Domain Processing - xiaohang • Wavelets - yangchen , wangcf • Image Restoration - wangcf • Image Compression - xiaoyong • Morphological Image Processing --- • Image Segmentation - xiaohang • Object Recognition --- yangchen

8. Frequency Domain Processing • The 2-D Discrete Fourier Transform • Filtering in the Frequency Domain

9. Wavelets • The Fast Wavelet Transform

10. Image Restoration • Noise Model • Restoration in the Presence of Noise Only – Spatial Filtering • Periodic Noise Reduction by Frequency Domain Filtering • Modeling the degradation Function • Direct Inverse Filtering • Wiener Filtering • Constrained Least Squares (Reqularized) Filtering • Iterative Nonlinear Restoration Using the Lucy-Richardson Algorithm • Blind Deconvolution • Geometric Transformations and Image Registration

11. Image Compression • Coding Redundancy • Interpixel Redundancy • Psychovisual Redundancy • JPEG Compression

12. Morphological Image Processing • Dilation and Erosion • Combining Dilation and Erosion • Labeling Connected Components • Morphological Reconstruction • Gray-Scale Morphology

13. Image Segmentation • Point, Line, and Edge Detection • Line Detection Using the Hough Transform • Thresholding • Region-Based Segmentation • Segmentation Using the Watershed Transform

14. Object Recognition • Computing Distance Measures • Recognition Based on Decision-Theoretic Methods • Structural Recognition

15. V3d-Convert

16. V3d-Convertsearch Search v3d_convert –list -help -list -search -history -component-tree-print -component-tree-create -component-tree-trim -component-tree-filter -component-tree-image -component-tree-dot -coseg-tree -coseg-image … ~ 167 cmds Search v3d_convert -fastm Do you mean -fastmarching 1: -fastmarching-linker 2: -fastmarching-mst 3: -fastmarching-phi 4: -fastmarching-tracing 5: -fastmarching-tree 6: -fastmarching-voronoi choose : [1] Search v3d_convert –search swc –l 3 1 : -swc-adjust 2 : -swc-connect 3 : -swc-filter 4 : -swc-split 5 : -swc-stat 6 : -swc2marker 7 : -swc2svm 8 : -help bipartite-matching 9 : -help chanvese 10 : -help circle-forward … 29 : -help swc-filter 30 : -help swc-stat 31 : -help swc2marker 32 : -help swc2svm 33 : -help trace-between

17. V3d-Convertabbreviation and history Abbreviation v3d_convert –topology-analysis rubin.tif –inswcta.swc v3d_convert –ta rubin.tif –is ta.swc v3d_convert –tparubin.tif –is ta.swc … History v3d_convert -history 1: v3d_convert -img 2: v3d_convert -img-erode 3: v3d_convert -img-erode 4: v3d_convert -img-erode 5: v3d_convert -search 6: v3d_convert -search good 7: v3d_convert -search filter 8: v3d_convert -search filter -l 3 9: v3d_convert -component-tree-filter 10: v3d_convert -mask

18. V3d-Convert Organization Parameter Attribute {"+component-tree-create",0},{"-mb",1},{"-Mb",1},{"-ma",1},{"-outtree",1},{"-bin",0} Run Func intrun_module(BasicParser & parser) { … if(cmd_name == "-component-tree-create") { … } … } Usage Func intmodule_usage(BasicParser & parser) { … if(cmd_name == "-component-tree-create") { … } … } With Usage v3d_convert -component-tree-create Usage : v3d_convert <img_file> -component-tree-create [-mb <int>] [-Mb <int>] [-ma <int>] [-outtree <tree_file>] create component tree and save to tree file -mb minimum beta size -Mb maximum beta size -ma minimum alpha size Without Usage v3d_convert -component-tree-create Usage : v3d_convert [<img_file>] -component-tree-create -mb <para> -Mb <para> -ma <para> -outtree <para> -bin

19. V3d-Convert and Vaa3D Parameter Attribute {"+component-tree-create",0},{"-mb",1},{"-Mb",1},{"-ma",1},{"-outtree",1},{"-bin",0}

20. V3d-Convert and ITK v3d_convert –itk 1: -itk-AntiAliasBinaryImageFilter 2: -itk-BSplineWarping1 3: -itk-BSplineWarping2 4: -itk-BilateralImageFilter 5: -itk-BinaryMedianImageFilter 6: -itk-BinaryMinMaxCurvatureFlowImageFilter 7: -itk-BinaryThinningImageFilter (~149 itkcmds) v3d_convert -itk-CannyEdgeDetectionImageFilter Usage: v3d_convert -itk-CannyEdgeDetectionImageFilterinputImageoutputImage [variance upperThresholdlowerThreshold]

21. Thanks!