Abstract

The sugarcane spot disease attack the sugarcane with appear as spots on the leaves, so this spots prevent the vital process of photosynthesis to take place and caused sugar production losses. Early diagnosis of this spot disease can improve the quality of sugar production. The diagnosis result can be used as decision reference to control the disease fast and accurately to minimize attack severe that can caused significant damage. Unfortunately, experts who are able to identify the diseases are often unavailable. This research attempted to identify the three sugarcane spot diseases (ring spot, rust spot, and yellow spot) using Segmentation-based Gray Level Co-Occurrence Texture (SGLCM) and LAB color moments. The SGLCM obtain 24 texture features of segmented image and color moments obtain 12 color features. This method achieved at least 93% accuracy when identifying the diseases using kNN classifier.

Original languageIndonesian
Pages (from-to)1-10
Number of pages10
JournalRegister: Jurnal Ilmiah Teknologi Sistem Informasi
Volume3
Issue number1
DOIs
Publication statusPublished - Jan 2017

Keywords

  • Color moments
  • GLCM
  • Segmentation
  • Spot disease
  • Sugarcane leaf image

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