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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...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2021
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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. |
format | Online Article Text |
id | pubmed-7867336 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
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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