Short review about sivp toolbox for Scilab

1. SIVP
Scilab Image and Video Processing Toolbox
Presented by Kelompok 2:
1. Edi Hartawan (18110876)
2. Frans Caisar Ramadhan (19110260)
3. Nurul An Nisa (15110202)
4. Satria Syahriful Muzakki (16110406)

2. What we’re gonna show
• What is Scilab?
• What is SIVP?
• How does it related?
• Sample code with usage
• Comparison with the other libraries
• Application Demo
• Live discussion

3. Scilab Quick Intro
• Distributed under GPL-compatible CeCILL license.
• Numerically Oriented Programming Language
• Can be used for signal processing, statistical analysis, image enhancement, fluid
dynamics simulations, numerical optimization, and modeling, simulation of explicit and
implicit dynamical systems and symbolic manipulations
• LaTeX engine
• Hundreds of Toolboxes
• Similar with Matlab
• Official Page www.scilab.org

4. SIVP Quick Intro
Scilab needs a powerful image processing toolbox. SIVP intends to do image
processing and video processing tasks. SIVP is meant to be a useful, efficient, and free
image and video processing toolbox for Scilab.
• Created in LIAMA - Institute of Automation - Shenzhen Institute of Advanced
Technology by Shiqi Yu, Jia Wu, Shulin Shang, and Vincent Etienne
• Developed based on OpenCV
• Current newest released version is SIVP 0.5.3
• Official Page http://atoms.scilab.org/toolboxes/SIVP

5. Scilab System Requirement
System Requirements: Windows® Optional
Software • An Internet connection for Scilab install with MKL
• Microsoft Windows XP (32 and 64 bits) • An Internet connection for ATOMS modules install
(using a proxy requires manual configuration of
• Windows Vista (32 and 64 bits) ATOMS)
• Windows 7 (32 and 64 bits) • A C compiler (Visual Studio 2010 or Visual Express
• Microsoft .NET Framework 7 2010) for C or C++ external modules compilation
and for Modelica use in Xcos
Hardware
• 2 Go RAM (1 Go minimum)
• 600 Mo hard disk space

6. Scilab System Requirement (i)
System Requirements: GNU/Linux • 2 Go RAM (1 Go minimum)
Software • 550 Mo hard disk space
• Debian (32 and 64 bits) Optional
• Redhat (32 and 64 bits) • An Internet connection for ATOMS modules install
(using a proxy requires manual configuration of
• Fedora (32 and 64 bits) ATOMS)
• Suse (32 and 64 bits) • A C compiler (gcc/clang) for C or C++ external
• Ubuntu (32 and 64 bits) modules compilation and for Modelica use in Xcos
• …. • A Fortran compiler (gfortran) for Fortran external
modules compilation
Hardware

7. Scilab System Requirement (ii)
System Requirements: Mac OS® • 500 Mo hard disk space
Software Optional
• Mac OS 10.5.x (Leopard®) • An Internet connection for ATOMS modules install
(using a proxy requires manual configuration of
• Mac OS 10.6.x (Snow Leopard®) ATOMS)
• Mac OS 10.7.x (Lion) • A C compiler (gcc/clang) for C or C++ external
• Mac OS X 10.8.x (Mountain Lion) modules compilation and for Modelica use in Xcos
Hardware • A Fortran compiler (gfortran) for Fortran external
modules compilation
• Mac Intel 64 bits processor
• 2 Go RAM (1 Go minimum)

8. SIVP Dependency and Requirement
Dependencies
• Scilab >= 3.1
• OpenCV >= 1.0.0
(if you want video support, OpenCV should be compiled with ffmpeg)

9. Powerful
Scilab + SIVP = Image and Video
Processing

10. Sample Code on Scilab
• Vector,Array dan Plot

11. Image Operations
• Read image into variable on Scilab:
• Rotation dan scalling

12. • Grayscale
• Gaussian Blur
• Segmentation by Threshold

13. ENJOY THE DEMONSTRATION

14. Other Image and Video Processing Library
• SIP (http://siptoolbox.sourceforge.net/)
• Image Processing Design Toolbox (http://atoms.scilab.org/toolboxes/IPD)
• Matlab (http://www.mathworks.com/products/matlab/)

15. Feature Comparison
SIP Matlab SIVP
The number of >90 15 10
supported
image format
The number of Unsupported 1 for Linux; 5 for About 50 (depends on
supported Windows the number of installed
video format codecs)
Open Source Yes No Yes
Source : sivp-doc

16. Benchmark Comparison
SIP Matlab SIVP
Reading 240 352×240 PNG 6.78s 6.04s 4.94s
color images, figure 13
Reading 240 352×240 PNG 1.85s 2.04s 0.24s
color images, figure 14
Sobel edge detection(512×512 0.34s 0.32s 0.04s
gray image), figure 15
Reading video frames(320×240 - 0.45s 0.31s
rawvideo, 100 frames), figure
16
Showing color image 0.19s 0.21s 0.95s
(512×512), figure 17
Source : sivp-doc

17. Performance Benchmark
Source : sivp-doc

18. Performance Benchmark
Source : sivp-doc

19. Resources
• SIVP Project Page (http://sourceforge.net/projects/sivp/)
• Scilab (http://www.scilab.org/)
• OpenCV (http://opencv.willowgarage.com/)
• SIP Toolbox (http://siptoolbox.sourceforge.net/)
• Free Software Association, Institute of Automation, Chinese Academy of
Sciences (http://fsa.ia.ac.cn/)