Publication:
Digital Image Sensor-Based Assessment of the Status of Oat (Avena sativa L.) Crops after Frost Damage

dc.contributor.authorMacedo Cruz, Antonia
dc.contributor.authorPajares Martinsanz, Gonzalo
dc.contributor.authorSantos, Matilde
dc.contributor.authorVillegas Romero, Isidro
dc.date.accessioned2023-06-20T01:07:25Z
dc.date.available2023-06-20T01:07:25Z
dc.date.issued2011-06-03
dc.description.abstractThe aim of this paper is to classify the land covered with oat crops, and the quantification of frost damage on oats, while plants are still in the flowering stage. The images are taken by a digital colour camera CCD-based sensor. Unsupervised classification methods are applied because the plants present different spectral signatures, depending on two main factors: illumination and the affected state. The colour space used in this application is CIELab, based on the decomposition of the colour in three channels, because it is the closest to human colour perception. The histogram of each channel is successively split into regions by thresholding. The best threshold to be applied is automatically obtained as a combination of three thresholding strategies: (a) Otsu’s method, (b) Isodata algorithm, and (c) Fuzzy thresholding. The fusion of these automatic thresholding techniques and the design of the classification strategy are some of the main findings of the paper, which allows an estimation of the damages and a prediction of the oat production.
dc.description.departmentDepto. de Ingeniería de Software e Inteligencia Artificial (ISIA)
dc.description.facultyFac. de Informática
dc.description.refereedTRUE
dc.description.sponsorshipMinisterio de Ciencia e Innovación (MICINN)
dc.description.sponsorshipCONACYT/Unión Europea
dc.description.statuspub
dc.eprint.idhttps://eprints.ucm.es/id/eprint/68462
dc.identifier.doi10.3390/s110606015
dc.identifier.issn1424-8220
dc.identifier.officialurlhttps://doi.org/10.3390/s110606015
dc.identifier.relatedurlhttps://www.mdpi.com/1424-8220/11/6/6015
dc.identifier.urihttps://hdl.handle.net/20.500.14352/43323
dc.issue.number6
dc.journal.titleSensors
dc.language.isoeng
dc.page.final6036
dc.page.initial6015
dc.publisherMDPI
dc.relation.projectIDDPI2009-14552-C02-01
dc.relation.projectIDFONCICYT 93829
dc.rightsAtribución 3.0 España
dc.rights.accessRightsopen access
dc.rights.urihttps://creativecommons.org/licenses/by/3.0/es/
dc.subject.keyworddigital image sensor
dc.subject.keywordagricultural images
dc.subject.keywordunsupervised classification
dc.subject.keywordautomatic thresholding
dc.subject.keywordCIELab colour space
dc.subject.keywordfuzzy error matrix
dc.subject.keywordoat frost damage
dc.subject.ucmInteligencia artificial (Informática)
dc.subject.unesco1203.04 Inteligencia Artificial
dc.titleDigital Image Sensor-Based Assessment of the Status of Oat (Avena sativa L.) Crops after Frost Damage
dc.typejournal article
dc.volume.number11
dspace.entity.typePublication
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