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T1k+: A database for benchmarking color texture classification and retrieval methods

Academic Article
Publication Date:
2021
abstract:
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.
Iris type:
1.1 Articolo in rivista
Keywords:
Color and Texture; Color texture databases; Texture descriptors; Texture features; Texture recognition; Texture retrieval
List of contributors:
Cusano, C.; Napoletano, P.; Schettini, R.
Authors of the University:
CUSANO CLAUDIO
Handle:
https://iris.unipv.it/handle/11571/1388234
Full Text:
https://iris.unipv.it//retrieve/handle/11571/1388234/417912/sensors-21-01010.pdf
Published in:
SENSORS
Journal
  • Overview

Overview

URL

https://www.mdpi.com/1424-8220/21/3/1010
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