Klasifikasi gambar makanan jepang menggunakan pendekatan KAZE dan Machine Learning

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Published: Jul 5, 2021
DOI: https://doi.org/10.26740/jieet.v3n1.p8-10

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Singgih Putra Pratama
UPN Veteran Jawa Timur
Roby Sirojul A
UPN Veteran Jawa Timur
Ilham Ade W.S
UPN Veteran Jawa Timur
Rayhan Aulia
UPN Veteran Jawa Timur

Abstract

Belakangan ini gambar menjadi salah satu bidang penelitian yang populer. Ilmu komputer berusaha untuk mempelajari dan mengenali berbagai macam objek gambar. Dalam penelitian ini adalah klasifikasi gambar makanan jepang menggunakan KAZE dengan tujuan mengetahui seberapa efektif metode KAZE dalam hal ektraksi fitur guna menunjang klasifikasi makanan jepang. Dalam jurnal ini akan menggunakan KAZE dalam hal ektraksi fitur gambar, lalu menggunakan K-means dalam klusterting dan menggunakan KD-tree untuk image recognition. Nantinya percobaan akan menggunakan tiga tipe makanan Jepang yaitu nasi (rice), belut diatas nasi (eels on rice), Pilaf, dan Chicken-'n'-egg on rice. Dari hasil percobaan menunjukkan bahwa pengenalan objek gambar makanan Jepang menggunakan algoritma KAZE menunjukkan hasil yang cukup baik dengan tingkat akurasi sebesar 43,6%.

Article Details

Issue
Vol. 3 No. 1 (2019)
Section
Volume 03 Nomor 01

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References

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