Content-based emblem retrieval using Zernike moments

The problem of content-based image retrieval is becoming essential in many real-world applications, mostly due to the growth in size of modern image databases. In particular, this work addresses the retrieval of trademark emblems, which is key for detecting trademark infringement. A common approach...

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Detalles Bibliográficos
Autores principales:	Cura, E., Tepper, M., Mejail, M.
Formato:	SER
Materias:	Comparison metrics Complex moments Content based image retrieval Content-based Execution time Image database Real-world application Shape descriptors Trademark infringement Work Focus Zernike Zernike moments Computer vision Commerce Content based retrieval Image retrieval Signal reconstruction Pattern recognition
Acceso en línea:	http://hdl.handle.net/20.500.12110/paper_03029743_v6419LNCS_n_p79_Cura
Aporte de:	Biblioteca Digital - Facultad de Ciencias Exactas y Naturales (UBA) de Universidad de Buenos Aires

id	todo:paper_03029743_v6419LNCS_n_p79_Cura
record_format	dspace
spelling	todo:paper_03029743_v6419LNCS_n_p79_Cura2023-10-03T15:19:16Z Content-based emblem retrieval using Zernike moments Cura, E. Tepper, M. Mejail, M. Comparison metrics Complex moments Content based image retrieval Content-based Execution time Image database Real-world application Shape descriptors Trademark infringement Work Focus Zernike Zernike moments Comparison metrics Complex moments Content based image retrieval Content-based Image database Shape descriptors Trademark infringement Zernike moments Computer vision Commerce Content based retrieval Image retrieval Signal reconstruction Pattern recognition The problem of content-based image retrieval is becoming essential in many real-world applications, mostly due to the growth in size of modern image databases. In particular, this work addresses the retrieval of trademark emblems, which is key for detecting trademark infringement. A common approach that proved suitable for this task, is to encode emblems using shape descriptors and Zernike complex moments. This work focuses on their study, proposing a two-fold contribution. First, we present some modifications to Zernike complex moments and then we explore the use of different comparison metrics. Both have shown to report improvements in retrieved results and in execution time. © 2010 Springer-Verlag. Fil:Cura, E. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina. Fil:Tepper, M. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina. Fil:Mejail, M. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina. SER info:eu-repo/semantics/openAccess http://creativecommons.org/licenses/by/2.5/ar http://hdl.handle.net/20.500.12110/paper_03029743_v6419LNCS_n_p79_Cura
institution	Universidad de Buenos Aires
institution_str	I-28
repository_str	R-134
collection	Biblioteca Digital - Facultad de Ciencias Exactas y Naturales (UBA)
topic	Comparison metrics Complex moments Content based image retrieval Content-based Execution time Image database Real-world application Shape descriptors Trademark infringement Work Focus Zernike Zernike moments Comparison metrics Complex moments Content based image retrieval Content-based Image database Shape descriptors Trademark infringement Zernike moments Computer vision Commerce Content based retrieval Image retrieval Signal reconstruction Pattern recognition
spellingShingle	Comparison metrics Complex moments Content based image retrieval Content-based Execution time Image database Real-world application Shape descriptors Trademark infringement Work Focus Zernike Zernike moments Comparison metrics Complex moments Content based image retrieval Content-based Image database Shape descriptors Trademark infringement Zernike moments Computer vision Commerce Content based retrieval Image retrieval Signal reconstruction Pattern recognition Cura, E. Tepper, M. Mejail, M. Content-based emblem retrieval using Zernike moments
topic_facet	Comparison metrics Complex moments Content based image retrieval Content-based Execution time Image database Real-world application Shape descriptors Trademark infringement Work Focus Zernike Zernike moments Comparison metrics Complex moments Content based image retrieval Content-based Image database Shape descriptors Trademark infringement Zernike moments Computer vision Commerce Content based retrieval Image retrieval Signal reconstruction Pattern recognition
description	The problem of content-based image retrieval is becoming essential in many real-world applications, mostly due to the growth in size of modern image databases. In particular, this work addresses the retrieval of trademark emblems, which is key for detecting trademark infringement. A common approach that proved suitable for this task, is to encode emblems using shape descriptors and Zernike complex moments. This work focuses on their study, proposing a two-fold contribution. First, we present some modifications to Zernike complex moments and then we explore the use of different comparison metrics. Both have shown to report improvements in retrieved results and in execution time. © 2010 Springer-Verlag.
format	SER
author	Cura, E. Tepper, M. Mejail, M.
author_facet	Cura, E. Tepper, M. Mejail, M.
author_sort	Cura, E.
title	Content-based emblem retrieval using Zernike moments
title_short	Content-based emblem retrieval using Zernike moments
title_full	Content-based emblem retrieval using Zernike moments
title_fullStr	Content-based emblem retrieval using Zernike moments
title_full_unstemmed	Content-based emblem retrieval using Zernike moments
title_sort	content-based emblem retrieval using zernike moments
url	http://hdl.handle.net/20.500.12110/paper_03029743_v6419LNCS_n_p79_Cura
work_keys_str_mv	AT curae contentbasedemblemretrievalusingzernikemoments AT tepperm contentbasedemblemretrievalusingzernikemoments AT mejailm contentbasedemblemretrievalusingzernikemoments
_version_	1782030796339544064

Content-based emblem retrieval using Zernike moments

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