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Title:	KFuji RGB-DS database: Fuji apple multi-modal images for fruit detection with color, depth and range-corrected IR data
Author:	Gené Mola, Jordi; Vilaplana Besler, Verónica; Rosell Polo, Joan Ramon; Morros Rubió, Josep Ramon; Ruiz Hidalgo, Javier; Gregorio, Eduard
Other authors:	Universitat Politècnica de Catalunya. Departament de Teoria del Senyal i Comunicacions; Universitat Politècnica de Catalunya. GPI - Grup de Processament d'Imatge i Vídeo
Abstract:	This article contains data related to the research article entitle “Multi-modal Deep Learning for Fruit Detection Using RGB-D Cameras and their Radiometric Capabilities” [1]. The development of reliable fruit detection and localization systems is essential for future sustainable agronomic management of high-value crops. RGB-D sensors have shown potential for fruit detection and localization since they provide 3D information with color data. However, the lack of substantial datasets is a barrier for exploiting the use of these sensors. This article presents the KFuji RGB-DS database which is composed by 967 multi-modal images of Fuji apples on trees captured using Microsoft Kinect v2 (Microsoft, Redmond, WA, USA). Each image contains information from 3 different modalities: color (RGB), depth (D) and range corrected IR intensity (S). Ground truth fruit locations were manually annotated, labeling a total of 12,839 apples in all the dataset. The current dataset is publicly available at http://www.grap.udl.cat/publicacions/datasets.html.
Abstract:	Peer Reviewed
Subject(s):	-Àrees temàtiques de la UPC::Informàtica::Sistemes d'informació::Bases de dades -Àrees temàtiques de la UPC::Enginyeria agroalimentària::Indústries agroalimentàries::Productes d'origen vegetal -Àrees temàtiques de la UPC::Enginyeria de la telecomunicació::Processament del senyal::Processament de la imatge i del senyal vídeo -Apples -Deep learning -Digital video -Image processing--Digital techniques -Pomes -Aprenentatge profund -Vídeo digital -Imatges -- Processament -- Tècniques digitals
Rights:	Attribution-NonCommercial-NoDerivs 3.0 Spain http://creativecommons.org/licenses/by-nc-nd/3.0/es/
Document type:	Article - Submitted version Article
Published by:	Elsevier
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