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T1K+: A Database for Benchmarking Color Texture Classification and Retrieval Methods

In this paper we present T1K+, a very large, heterogeneous database of high-quality texture images acquired under variable conditions. T1K+ contains 1129 classes of textures ranging from natural subjects to food, textile samples, construction materials, etc. T1K+ allows the design of experiments esp...

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Detalles Bibliográficos
Autores principales: Cusano, Claudio, Napoletano, Paolo, Schettini, Raimondo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7867336/
https://www.ncbi.nlm.nih.gov/pubmed/33540828
http://dx.doi.org/10.3390/s21031010
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author Cusano, Claudio
Napoletano, Paolo
Schettini, Raimondo
author_facet Cusano, Claudio
Napoletano, Paolo
Schettini, Raimondo
author_sort Cusano, Claudio
collection PubMed
description In this paper we present T1K+, a very large, heterogeneous database of high-quality texture images acquired under variable conditions. T1K+ contains 1129 classes of textures ranging from natural subjects to food, textile samples, construction materials, etc. T1K+ allows the design of experiments especially aimed at understanding the specific issues related to texture classification and retrieval. To help the exploration of the database, all the 1129 classes are hierarchically organized in 5 thematic categories and 266 sub-categories. To complete our study, we present an evaluation of hand-crafted and learned visual descriptors in supervised texture classification tasks.
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spelling pubmed-78673362021-02-07 T1K+: A Database for Benchmarking Color Texture Classification and Retrieval Methods Cusano, Claudio Napoletano, Paolo Schettini, Raimondo Sensors (Basel) Article In this paper we present T1K+, a very large, heterogeneous database of high-quality texture images acquired under variable conditions. T1K+ contains 1129 classes of textures ranging from natural subjects to food, textile samples, construction materials, etc. T1K+ allows the design of experiments especially aimed at understanding the specific issues related to texture classification and retrieval. To help the exploration of the database, all the 1129 classes are hierarchically organized in 5 thematic categories and 266 sub-categories. To complete our study, we present an evaluation of hand-crafted and learned visual descriptors in supervised texture classification tasks. MDPI 2021-02-02 /pmc/articles/PMC7867336/ /pubmed/33540828 http://dx.doi.org/10.3390/s21031010 Text en © 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Cusano, Claudio
Napoletano, Paolo
Schettini, Raimondo
T1K+: A Database for Benchmarking Color Texture Classification and Retrieval Methods
title T1K+: A Database for Benchmarking Color Texture Classification and Retrieval Methods
title_full T1K+: A Database for Benchmarking Color Texture Classification and Retrieval Methods
title_fullStr T1K+: A Database for Benchmarking Color Texture Classification and Retrieval Methods
title_full_unstemmed T1K+: A Database for Benchmarking Color Texture Classification and Retrieval Methods
title_short T1K+: A Database for Benchmarking Color Texture Classification and Retrieval Methods
title_sort t1k+: a database for benchmarking color texture classification and retrieval methods
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7867336/
https://www.ncbi.nlm.nih.gov/pubmed/33540828
http://dx.doi.org/10.3390/s21031010
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