Identification and classification of the quality of snake fruit using image processing techniques: A computer vision approach

Mansur As; Baharuddin; Siti Subaedah; Andi Bahar; Ismail Parewai

doi:10.1063/5.0295836

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Identification and classification of the quality of snake fruit using image processing techniques: A computer vision approach

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Mansur As, Baharuddin, Siti Subaedah, Andi Bahar, Ismail Parewai

2025 AIP Conference Proceedings Vol. 3316 Issue 1 Conference paper Cited by 0 SDG 17SDG 8SDG 16

Abstract

This study aims to provide an accurate model of image processing techniques for inspecting and classifying fruit quality. A Computer Vision System (visible and invisible channels) was proposed to analyze the external texture. We first identified and analyzed the characteristics of the external texture of snake fruit using the Grey Level Co-occurrence Matrix (GLCM) method and ImageJ tool. Then, the grade quality will be classified using Random Forest (RF) methods. This study showed that the Computer Vision system is helpful for the assessment and classification of the snake fruit quality. The experiment also indicates that the combination of the visible and invisible channels has the potential in fruit inspection models in image processing techniques since the hidden texture features are not clearly visible to the human eye. © 2025 Author(s).

Affiliations

Universitas Negeri Medan, Medan, Indonesia; Kyushu Institute of Technology, Kitakyushu, Japan

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