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Shape Similarity Image Retrieval by Hypothesis and Test
Cambridge UK August 23-August 26
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/ICPR.2004.133443217th International Conference on Patt ...
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Enver Sangineto, "Shape Similarity Image Retrieval by Hypothesis and Test," Pattern Recognition, International Conference on, vol. 2, pp. 1017-1020, 17th International Conference on Pattern Recognition (ICPR'04) - Volume 2, 2004.
 
 
BibTex
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@article{ 10.1109/ICPR.2004.1334432,
author = {Enver Sangineto},
title = {Shape Similarity Image Retrieval by Hypothesis and Test},
journal ={Pattern Recognition, International Conference on},
volume = {2},
year = {2004},
issn = {1051-4651},
pages = {1017-1020},
doi = {http://doi.ieeecomputersociety.org/10.1109/ICPR.2004.1334432},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
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TY - CONF
JO - Pattern Recognition, International Conference on
TI - Shape Similarity Image Retrieval by Hypothesis and Test
SN - 1051-4651
SP1017
EP1020
A1 - Enver Sangineto,
PY - 2004
KW - null
VL - 2
JA - Pattern Recognition, International Conference on
ER -
 
Enver Sangineto, Centro di Ricerca in Matematica Pura e Applicata (CRMPA), Italy
Image Retrieval by shape similarity systems usually either focus their attention on images with isolated objects (uniform backgrounds and no occluding objects) or perform time consuming exhaustive initializations to localize the portion of the image possibly containing the searched shape. We propose a Content Based Image Retrieval (CBIR) method merging classic alignment techniques for an efficient shape localization with an innovative verification strategy able to deal with an inexact matching between the searched and the found shape.
Citation:
Enver Sangineto, "Shape Similarity Image Retrieval by Hypothesis and Test," icpr, vol. 2, pp.1017-1020, 17th International Conference on Pattern Recognition (ICPR'04) - Volume 2, 2004
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