Detection of aflatoxin contamination in corn using The Simplified Gabor Wavelet algorithm

Dublin Core

Title

Detection of aflatoxin contamination in corn using The Simplified Gabor Wavelet algorithm

Subject

corn quality
image processing
aflatoxin
detection

Description

The quality of corn is essential to determine whether the corn is still suitable for consumption and what type of corn it is. Corn is one type of vegetable that is indispensable for the nutritional needs of the Indonesian people today and is a mixture of other essential ingredients. Corn is rich in fiber, which is good for improving digestion and overcoming constipation, controlling blood sugar levels, maintaining heart health, overcoming depression, maintaining eye health, and preventing diverticulitis. In this research, image recognition is used to determine and detect the content of aflatoxin, which is one type of abnormality or disorder in corn. This affects the quality of corn, whether corn is suitable for human consumption, and what impact aflatoxin has on the human body. on testing using parameters Non UV image, SGW Filter Image θ = 0, 90, 180 and 270, and The resulting SGW image with the number of orientations N = 4, θ = θ + pi/N, and θ = θ + 2*pi/N, The aflatoxin content in humans can cause carcinogenic or liver cancer and acute necrosis, cirrhosis, and carcinoma in the animal liver.

Creator

Yudistiro, Kukuh
Gatot Suharto Abdul Fatah
Lasinta Ari Nendra Wibawa
Prastiyono, Yudi

Source

Internet of Things and Artificial Intelligence Journal; Vol. 3 No. 1 (2023): Vol. 3 No.1 (2023): Volume 3 Issue 1, 2023 [February]; 19-32
2774-4353

Publisher

Association for Scientific Computing, Electronics, and Engineering (ASCEE)

Date

2023-02-01

Rights

Copyright (c) 2023 ascee
https://ascee.org/

Relation

Format

application/pdf

Language

eng

Type

info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion

Identifier

Citation

Kukuh Yudistiro et al., Detection of aflatoxin contamination in corn using The Simplified Gabor Wavelet algorithm, Association for Scientific Computing, Electronics, and Engineering (ASCEE), 2023, accessed November 5, 2024, https://igi.indrastra.com/items/show/812

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