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2009 XXII Brazilian Symposium on Computer Graphics and Image Processing
A Comparative Study among Pattern Classifiers in Interactive Image Segmentation
Rio de Janeiro, Brazil
October 11-October 15
ISBN: 978-0-7695-3813-6
ASCII Text
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Thiago V. Spina, Javier A. Montoya-Zegarra, Fábio Andrijauskas, Fábio A. Faria, Carlos E.A. Zampieri, Sheila M. Pinto-Cáceres, Tiago J. de Carvalho, Alexandre X. Falcão, "A Comparative Study among Pattern Classifiers in Interactive Image Segmentation," Graphics, Patterns and Images, SIBGRAPI Conference on, pp. 268-275, 2009 XXII Brazilian Symposium on Computer Graphics and Image Processing, 2009.
 
 
BibTex
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@article{ 10.1109/SIBGRAPI.2009.45,
author = {Thiago V. Spina and Javier A. Montoya-Zegarra and Fábio Andrijauskas and Fábio A. Faria and Carlos E.A. Zampieri and Sheila M. Pinto-Cáceres and Tiago J. de Carvalho and Alexandre X. Falcão},
title = {A Comparative Study among Pattern Classifiers in Interactive Image Segmentation},
journal ={Graphics, Patterns and Images, SIBGRAPI Conference on},
volume = {0},
year = {2009},
issn = {1530-1834},
pages = {268-275},
doi = {http://doi.ieeecomputersociety.org/10.1109/SIBGRAPI.2009.45},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
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TY - CONF
JO - Graphics, Patterns and Images, SIBGRAPI Conference on
TI - A Comparative Study among Pattern Classifiers in Interactive Image Segmentation
SN - 1530-1834
SP268
EP275
A1 - Thiago V. Spina,
A1 - Javier A. Montoya-Zegarra,
A1 - Fábio Andrijauskas,
A1 - Fábio A. Faria,
A1 - Carlos E.A. Zampieri,
A1 - Sheila M. Pinto-Cáceres,
A1 - Tiago J. de Carvalho,
A1 - Alexandre X. Falcão,
PY - 2009
KW - Pattern classifiers
KW - graph-based image segmentation
KW - image foresting transform
KW - fuzzy classification
VL - 0
JA - Graphics, Patterns and Images, SIBGRAPI Conference on
ER -
 
Edition of natural images usually asks for considerable userinvolvement, being segmentation one of the main challenges. This paper describes an unified graph-based framework for fast, precise and accurate interactive image segmentation. The method divides segmentation into object recognition, enhancement and extraction. Recognition is done by the user when markers are selected inside and outside the object. Enhancement increases the dissimilarities between object and background and Extraction separates them. Enhancement is done by a fuzzy pixel classifier and it has a great impact in the number of markers required for extraction. In view of minimizing user involvement, we focus this paper on a comparative study among popular classifiers for enhancement, conducting experiments with several natural images and seven users.
Index Terms:
Pattern classifiers, graph-based image segmentation, image foresting transform, fuzzy classification
Citation:
Thiago V. Spina, Javier A. Montoya-Zegarra, Fábio Andrijauskas, Fábio A. Faria, Carlos E.A. Zampieri, Sheila M. Pinto-Cáceres, Tiago J. de Carvalho, Alexandre X. Falcão, "A Comparative Study among Pattern Classifiers in Interactive Image Segmentation," sibgrapi, pp.268-275, 2009 XXII Brazilian Symposium on Computer Graphics and Image Processing, 2009
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