loading...
 This Article 
   
 Share 
   
 Bibliographic References 
   
 Add to: 
 
Digg
Furl
Spurl
Blink
Simpy
Google
Del.icio.us
Y!MyWeb
 
 Search 
   
2009 Ninth International Conference on Intelligent Systems Design and Applications
A A-IFSs Based Image Segmentation Methodology for Gait Analysis
Pisa, Italy
November 30-December 02
ISBN: 978-0-7695-3872-3
ASCII Text
x 
 
Pedro Couto, Vitor Filipe, Pedro Melo-Pinto, Humberto Bustince, Edurne Barrenechea, "A A-IFSs Based Image Segmentation Methodology for Gait Analysis," Intelligent Systems Design and Applications, International Conference on, pp. 1318-1323, 2009 Ninth International Conference on Intelligent Systems Design and Applications, 2009.
 
 
BibTex
x
 
@article{ 10.1109/ISDA.2009.44,
author = {Pedro Couto and Vitor Filipe and Pedro Melo-Pinto and Humberto Bustince and Edurne Barrenechea},
title = {A A-IFSs Based Image Segmentation Methodology for Gait Analysis},
journal ={Intelligent Systems Design and Applications, International Conference on},
volume = {0},
year = {2009},
isbn = {978-0-7695-3872-3},
pages = {1318-1323},
doi = {http://doi.ieeecomputersociety.org/10.1109/ISDA.2009.44},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
x 
 
TY - CONF
JO - Intelligent Systems Design and Applications, International Conference on
TI - A A-IFSs Based Image Segmentation Methodology for Gait Analysis
SN - 978-0-7695-3872-3
SP1318
EP1323
A1 - Pedro Couto,
A1 - Vitor Filipe,
A1 - Pedro Melo-Pinto,
A1 - Humberto Bustince,
A1 - Edurne Barrenechea,
PY - 2009
KW - image segmentation
KW - fuzzy logic
KW - Atanassov's intuitionistic fuzzy sets
VL - 0
JA - Intelligent Systems Design and Applications, International Conference on
ER -
 
In this work, image segmentation is addressed as the starting point within a motion analysis methodology intended for biomechanics behavior characterization. First, we propose a general segmentation framework that uses Atanassov’s intuitionistic fuzzy sets (A-IFSs) to determine the optimal image threshold value. Atanassov’s intuitionistic fuzzy index values are used for representing the unknowledge/ignorance of an expert on determining whether a pixel belongs to the background or the object of the image. Then, we introduce an extension of this methodology that uses a heuristic based multi-threshold approach to determine the optimal threshold. Experimental results are presented.
Index Terms:
image segmentation, fuzzy logic, Atanassov's intuitionistic fuzzy sets
Citation:
Pedro Couto, Vitor Filipe, Pedro Melo-Pinto, Humberto Bustince, Edurne Barrenechea, "A A-IFSs Based Image Segmentation Methodology for Gait Analysis," isda, pp.1318-1323, 2009 Ninth International Conference on Intelligent Systems Design and Applications, 2009
Usage of this product signifies your acceptance of the Terms of Use.