ANOTASI CITRA MULTISPEKTRAL UNTUK PEMBANGUNAN DATASET MODEL DETEKSI OBJEK PADA KEMATANGAN TANDAN BUAH SEGAR KELAPA SAWIT

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dc.contributor.authorHarmailil, Ihsan Okta
dc.contributor.supervisorMinarni, Minarni
dc.date.accessioned2023-06-21T02:19:25Z
dc.date.available2023-06-21T02:19:25Z
dc.date.issued2023-04
dc.description.abstractComputer vision as an object detection method can be used as a basis for automation process of sorting and grading oil palm FFB (Fresh Fruit Bunches). Images annotation are necessary to build datasets hence object detection model can identify object features in images. This study aims to annotate multispectral images of oil palm FFB with 2 categories, namely ripe and unripe FFB. Image acquisition is carried out with LED-based multispectral imaging system. Annotation is done using the python program application, called Labelimg. The number of annotated image data is 60 images consist of 30 images of ripe FFB and 30 images of unripe FFB. The results of annotation are .txt files contained information about bounding box coordinate, class object, and image dimension.en_US
dc.description.sponsorshipJurusan Fisika, Fakultas Matematika dan Ilmu Pengetahuan Alam, Universitas Riauen_US
dc.identifier.citationPerpustakaanen_US
dc.identifier.otherElfitra
dc.identifier.urihttps://repository.unri.ac.id/handle/123456789/11028
dc.language.isoenen_US
dc.publisherElfitraen_US
dc.subjectComputer visionen_US
dc.subjectannotationen_US
dc.subjectmultispectral imagesen_US
dc.subjectvoil palm FFBen_US
dc.titleANOTASI CITRA MULTISPEKTRAL UNTUK PEMBANGUNAN DATASET MODEL DETEKSI OBJEK PADA KEMATANGAN TANDAN BUAH SEGAR KELAPA SAWITen_US
dc.typeArticleen_US

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