Grape Maturity Estimation Using Time-of-Flight and LiDAR Depth Cameras

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aut.relation.issue16
aut.relation.journalSensors
aut.relation.volume24
dc.contributor.authorLegg, Mathew
dc.contributor.authorParr, Baden
dc.contributor.authorPascual, Genevieve
dc.contributor.authorAlam, Fakhrul
dc.date.accessioned2024-08-09T03:06:42Z
dc.date.available2024-08-09T03:06:42Z
dc.date.issued2024-08-07
dc.description.abstractThis article investigates the potential for using low-cost depth cameras to estimate the maturity of green table grapes after they have been harvested. Time-of-flight (Kinect Azure) and LiDAR (Intel L515) depth cameras were used to capture depth scans of green table grape berries over time. The depth scans of the grapes are distorted due to the diffused scattering of the light emitted from the cameras within the berries. This causes a distance bias where a grape berry appears to be further from the camera than it is. As the grape aged, the shape of the peak corresponding to the grape became increasingly flattened in shape, resulting in an increased distance bias over time. The distance bias variation with time was able to be fitted with an 𝑅2 value of 0.969 for the Kinect Azure and an average of 0.904 for the Intel L515. This work shows that there is potential to use time-of-flight and LIDAR cameras for estimating grape maturity postharvest in a non-contact and nondestructive manner.
dc.identifier.citationSensors, ISSN: 1424-8220 (Print); 1424-3210 (Online), MDPI AG, 24(16). doi: 10.3390/s24165109
dc.identifier.doi10.3390/s24165109
dc.identifier.issn1424-8220
dc.identifier.issn1424-3210
dc.identifier.urihttp://hdl.handle.net/10292/17862
dc.publisherMDPI AG
dc.relation.urihttps://www.mdpi.com/1424-8220/24/16/5109
dc.rights© 2024 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 (https://creativecommons.org/licenses/by/4.0/).
dc.rights.accessrightsOpenAccess
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.subject0301 Analytical Chemistry
dc.subject0502 Environmental Science and Management
dc.subject0602 Ecology
dc.subject0805 Distributed Computing
dc.subject0906 Electrical and Electronic Engineering
dc.subjectAnalytical Chemistry
dc.subject3103 Ecology
dc.subject4008 Electrical engineering
dc.subject4009 Electronics, sensors and digital hardware
dc.subject4104 Environmental management
dc.subject4606 Distributed computing and systems software
dc.titleGrape Maturity Estimation Using Time-of-Flight and LiDAR Depth Cameras
dc.typeJournal Article
pubs.elements-id564786
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