Comparative Framework Review Of Image Processing Software

Comparative Framework Review of Image Processing Software By Priyanka Desai GCIS 546 Managing Information Organization Professor Brain Scott

Introduction Image Processing  

Introduction: Applications Image Processing Computer vision Face detection Feature detection Lane departure warning system Non-photorealistic rendering Medical image processing Microscope image processing Morphological image processing Remote sensing 

Introduction: Operations Geometric transformation of image - scale,

rotate, translate Color correction – brightness, contrast variation, color space modification Compositing – combining two or more images Image editing – to enhance the quality of image Image segmentation – used to partition the image in smaller segments Image recognition – patterns in the image can be recognized 

Objective Study Image processing frameworks having

both ITK, VTK Like SCIRun,Volview, Matlab, MeVisLab, MITK. Compare functionality of each software Benefits & limitations: User and developers view Conclusion 

Background: Toolkits ITK (Insight toolkit) VTK (Visualization toolkit) Open Source 

SCIRun: Power Apps Developement Enviroment C/C++ , Integrated developement

enviroment(IDE) with visula data flow programming Modules 600+ Modules Interface: Matlab, C/C++ programs  BioTensor BioFEM BioImage

Volview  Development Enviroment:Menu+GUI panels no

programming Modules : 37 ITK+VTK filters Interface: Plugins are available Medical Application

Matlab Development Enviroment: Visual data

programming, ,command line, S- Function. Modules: 600+ Interface: DLL, C/C++,Executable, Java, Excel General and Specialized for all applications

MeVisLab Development Environment:Visual data

prgramming Modules: 500 Interface: C/C++, macro modules, OpenGL,SCIRun PowerApp, Java Script

MITK Development Environment C/C++ library Modules : vary Applications: Medical+ Non Medical Interface: Easy and customizable 

Functionality Color and Opacity Transfer Function Volume

Rendering e.g. CT of fractures bones, distributions of snow or rain clouds Gradient Magnitude Transfer Function Volume Rendering  e.g. luggage scan, cancer tumors in a human liver Multidimensional Transfer Function Volume Rendering  e.g. Tooth in CT, visualize explosion simulation results Tagged Volume Rendering  e.g. pistons inside an engine block

Functionality Finite Element Analysis e.g. accidental fire and

explosion simulations Partial Differential equation 3D Deformable Mesh Segmentation 3D Sampled Data Exploration Interactive Segmentation Parameter Finding Interactive Prototyping of Research Algorithms Analysis of3D + Time Volume Data  

Reference Example Spine Detection Seed points Edge Detection, Background subtraction Spine Axis calculation

Reference Example: Result

SCIRun

MeVislab

MITK

VolView

Matlab

Developer view of Comparison Application SCIRun Developer Criteria

MITK

VolView

MeVisLab

Matlab

Total

5

-3

2

6

2

User View of Comparison Application User Evaluation Criteria SCIRun MITK VolView MeVisLab MatLab Total

7

-4

-5

8

18

Conclusion Matlab scores higher in User and developer’s

criteria Specialized in Medical and non medical image data Total package of Image acquisition toolbox and Video processing block-set. 