Abstract

In 2019 the yield of rice production experienced a considerable decline, one of which was caused by weather factors that resulted in drought on the land, so that the absorption of nutrients given to rice plants was not optimal. Seeing developments in the field of image technology, researchers used image processing and computer vision to determine the availability of nutrients contained in the image of rice leaves, by applying the feature extraction method. Feature extraction produces six feature values which are then used for detection using the Learning Vector Quantization (LVQ) method. The detection in this final project can recognize the image of rice plants lacking in nutrients N, P, and K which has an accuracy of 87.5

Original languageEnglish
Title of host publication2021 International Conference on Advanced Mechatronics, Intelligent Manufacture and Industrial Automation, ICAMIMIA 2021 - Proceeding
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages143-148
Number of pages6
ISBN (Electronic)9781665499699
DOIs
Publication statusPublished - 2021
Event2021 International Conference on Advanced Mechatronics, Intelligent Manufacture and Industrial Automation, ICAMIMIA 2021 - Surabya, Indonesia
Duration: 8 Dec 20219 Dec 2021

Publication series

Name2021 International Conference on Advanced Mechatronics, Intelligent Manufacture and Industrial Automation, ICAMIMIA 2021 - Proceeding

Conference

Conference2021 International Conference on Advanced Mechatronics, Intelligent Manufacture and Industrial Automation, ICAMIMIA 2021
Country/TerritoryIndonesia
CitySurabya
Period8/12/219/12/21

Keywords

  • feature extraction
  • image processing
  • learning vector quantization
  • nutrients
  • rice leaf image

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