SIVPScilab 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)

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

Scilab Quick Intro

• Distributed under GPL-compatible CeCILL license.

• Numerically Oriented Programming Language

• Can be used for signal processing, statistical analysis, image enhancement, fluiddynamics simulations, numerical optimization, and modeling, simulation of explicit andimplicit dynamical systems and symbolic manipulations

• LaTeX engine

• Hundreds of Toolboxes

• Similar with Matlab

• Official Page www.scilab.org

SIVP Quick Intro

Scilab needs a powerful image processing toolbox. SIVP intends to do imageprocessing and video processing tasks. SIVP is meant to be a useful, efficient, and freeimage and video processing toolbox for Scilab.

• Created in LIAMA - Institute of Automation - Shenzhen Institute of AdvancedTechnology 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

Scilab System Requirement

System Requirements: Windows®

Software

• Microsoft Windows XP (32 and 64 bits)

• Windows Vista (32 and 64 bits)

• Windows 7 (32 and 64 bits)

• Microsoft .NET Framework 7

Hardware

• 2 Go RAM (1 Go minimum)

• 600 Mo hard disk space

Optional

• An Internet connection for Scilab install with MKL

• An Internet connection for ATOMS modules install (using a proxy requires manual configuration of ATOMS)

• A C compiler (Visual Studio 2010 or Visual Express 2010) for C or C++ external modules compilation and for Modelica use in Xcos

Scilab System Requirement (i)

System Requirements: GNU/Linux

Software

• Debian (32 and 64 bits)

• Redhat (32 and 64 bits)

• Fedora (32 and 64 bits)

• Suse (32 and 64 bits)

• Ubuntu (32 and 64 bits)

• ….

Hardware

• 2 Go RAM (1 Go minimum)

• 550 Mo hard disk space

Optional

• An Internet connection for ATOMS modules install (using a proxy requires manual configuration of ATOMS)

• A C compiler (gcc/clang) for C or C++ external modules compilation and for Modelica use in Xcos

• A Fortran compiler (gfortran) for Fortran external modules compilation

Scilab System Requirement (ii)

System Requirements: Mac OS®

Software

• Mac OS 10.5.x (Leopard®)

• Mac OS 10.6.x (Snow Leopard®)

• Mac OS 10.7.x (Lion)

• Mac OS X 10.8.x (Mountain Lion)

Hardware

• Mac Intel 64 bits processor

• 2 Go RAM (1 Go minimum)

• 500 Mo hard disk space

Optional

• An Internet connection for ATOMS modules install (using a proxy requires manual configuration of ATOMS)

• A C compiler (gcc/clang) for C or C++ external modules compilation and for Modelica use in Xcos

• A Fortran compiler (gfortran) for Fortran external modules compilation

SIVP Dependency and Requirement

Dependencies

• Scilab >= 3.1

• OpenCV >= 1.0.0

(if you want video support, OpenCV should be compiled with ffmpeg)

Scilab + SIVP =

Powerful

Image and Video

Processing

Sample Code on Scilab

• Vector,Array dan Plot

Image Operations

• Read image into variable on Scilab:

• Rotation dan scalling

• Grayscale

• Gaussian Blur

• Segmentation by Threshold

ENJOY THE DEMONSTRATION

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/)

Feature Comparison

SIP Matlab SIVP

The number of

supported

image format

>90 15 10

The number of

supported

video format

Unsupported 1 for Linux; 5 for

Windows

About 50 (depends on

the number of installed

codecs)

Open Source Yes No Yes

Source : sivp-doc

Benchmark ComparisonSIP Matlab SIVP

Reading 240 352×240 PNG

color images, figure 13

6.78s 6.04s 4.94s

Reading 240 352×240 PNG

color images, figure 14

1.85s 2.04s 0.24s

Sobel edge detection(512×512

gray image), figure 15

0.34s 0.32s 0.04s

Reading video frames(320×240

rawvideo, 100 frames), figure

16

- 0.45s 0.31s

Showing color image

(512×512), figure 17

0.19s 0.21s 0.95s

Source : sivp-doc

Performance Benchmark

Source : sivp-doc

Performance Benchmark

Source : sivp-doc

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/)