ICSM Group meetingHang XiaoOct 18, 2012

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

Regular StudyBooks

《 Digital Image Processing 》

《 Machine Vision Theory, Algorithms, Practicalities 》

Tools ITK OpenCV

Paper Presentation 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

Image processing journals

Paper Presentation Journals

Pattern Recognition, 3.172

Journal of Machine Learning Research, 2.682

Data Mining and Knowledge Discovery, 1.545

…

Machine learning journals

Paper Presentation Conferences

CVPR: IEEE Computer Vision and Pattern Recognition

ICIP : IEEE Internal Conference on Image Processing

ICASSP: ICCV: International Conference on Computer

VisionACCV: Asian Conference on Computer Vision

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

Frequency Domain Processing

The 2-D Discrete Fourier TransformFiltering in the Frequency Domain

Wavelets

The Fast Wavelet Transform

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

Image Compression

Coding Redundancy Interpixel RedundancyPsychovisual Redundancy JPEG Compression

Morphological Image Processing

Dilation and ErosionCombining Dilation and ErosionLabeling Connected ComponentsMorphological ReconstructionGray-Scale Morphology

Image Segmentation

Point, Line, and Edge DetectionLine Detection Using the Hough TransformThresholdingRegion-Based SegmentationSegmentation Using the Watershed Transform

Object Recognition

Computing Distance MeasuresRecognition Based on Decision-Theoretic

MethodsStructural Recognition

V3d-Convert

• Search• Abbreviation• History• 54291 line

• demo/demo.pro• demo/run_demo.h• demo/Run_demo.cpp

• Easy to use• Easy to write• Easy to manage• Easy to transfer

• 2d->3d convert• Algorithm collection /testing

Motivation Principle

AdvantageOrganization

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 –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

Search

v3d_convert -fastmDo you mean -fastmarching

1: -fastmarching-linker 2: -fastmarching-mst 3: -fastmarching-phi 4: -fastmarching-tracing 5: -fastmarching-tree 6: -fastmarching-voronoi

choose : [1]

V3d-Convertsearch

Abbreviation

v3d_convert –topology-analysis rubin.tif –inswc ta.swc

v3d_convert –ta rubin.tif –is ta.swc

v3d_convert –tpa rubin.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

V3d-Convertabbreviation and history

V3d-Convert Organization Parameter Attribute {"+component-tree-create",0},{"-mb",1},{"-Mb",1},{"-ma",1},{"-outtree",1},{"-bin",0} Usage Func

int module_usage(BasicParser & parser){… if(cmd_name == "-component-tree-create") {

… }…}

Run Func int run_module(BasicParser & parser){… if(cmd_name == "-component-tree-create") {

… }…}

With Usagev3d_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 Usagev3d_convert -component-tree-create

Usage :

v3d_convert [<img_file>] -component-tree-create -mb <para> -Mb <para> -ma <para> -outtree <para> -bin

V3d-Convert and Vaa3D

Parameter Attribute {"+component-tree-create",0},{"-mb",1},{"-Mb",1},{"-ma",1},{"-outtree",1},{"-bin",0}

V3d-Convert and ITKv3d_convert –itk 1: -itk-AntiAliasBinaryImageFilter 2: -itk-BSplineWarping1 3: -itk-BSplineWarping2 4: -itk-BilateralImageFilter 5: -itk-BinaryMedianImageFilter 6: -itk-BinaryMinMaxCurvatureFlowImageFilter 7: -itk-BinaryThinningImageFilter (~149 itk cmds)

v3d_convert -itk-CannyEdgeDetectionImageFilterUsage: v3d_convert -itk-CannyEdgeDetectionImageFilter inputImage outputImage [variance upperThreshold lowerThreshold]

Thanks!