IDENTIFIKASI CITRA DAUN TANAMAN JERUK DENGAN LOCAL BINARY PATTERN DAN MOMENT INVARIANT

Ayu Novitasari, Endina Putri Purwandari, Funny Farady Coastera

Abstract


Citrus species identification can use from citrus leaf image. The research purposes build the identificate citrus species based on leaf texture and shape by using Local Binary Pattern as texture feature and Moment Invariant as shape feature, and Euclidean Distance as image distance measurement. The research data use citrus leaf image consist of Citrus aurantifolia, Citrus sinesis, Citrus hystrix, Citrus limon, Citrus maxima, Citrus amblycarpa, and Citrus microcarpa. Based on experiment tests, we can conclude that (1) 100% accuracy for citrus leaf from a smartphone, (2) 100% accuracy for citrus leaf from a smartphone with red background, (3) 85,71% accuracy for citrus leaf from a smartphone with green background, (4) 100% accuracy for citrus leaf from a smartphone with blue background, (5) 85,71% accuracy for citrus leaf from a smartphone with black background, (6) 85,71% for images from the internet.


Keywords


citrus; identification; leaf; local binary pattern; moment invariant

Full Text:

PDF


DOI: http://dx.doi.org/10.26798/jiko.v3i2.141

Article Metrics

Abstract view : 420 times
PDF - 3098 times

Refbacks

  • There are currently no refbacks.




Copyright (c) 2018 Ayu Novitasari, Endina Putri Purwandari, Funny Farady Coastera


JIKO (Jurnal Informatika dan Komputer)

Published by
Lembaga Penelitian dan Pengabdian Masyarakat
Universitas Teknologi Digital Indonesia (d.h STMIK AKAKOM)

Jl. Raya Janti (Majapahit) No. 143 Yogyakarta, 55198
Telp. (0274)486664

Website : https://www.utdi.ac.id/

e-ISSN : 2477-3964 
p-ISSN : 2477-4413