Mung Beans Quality Detection Using Machine Vision

Christian, Yongky Felix and Rusyadi, Rusman and Rusli, Leonard P. (2021) Mung Beans Quality Detection Using Machine Vision. Bachelor thesis, Swiss German University.

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Abstract

Industry era is moving rapidly, and every year there is a demand for more efficient way to produce new things. Especially in Indonesia as a agriculture country, the demand in agriculture Industry of more automation is increasing. This thesis objective is to find a way to detect a mung beans in a efficient way, so in the future can reduce a manual sorting and produce a more high quality beans in an efficient way. Machine vision will be implemented in this project and find what method of machine vision will be optimal for mung beans detection. Machine learning that a part of machine vision will be tested as well to see the performance in this project. The main concept is to use a camera as the image capture tools, then send the input to computer for image processing. If the computer detects a bad bean, it will send a command to the ejector to eliminate these bad beans.

Item Type: Thesis (Bachelor)
Uncontrolled Keywords: Machine Vision, Machine Learning, Mung beans sorter, Object Detection
Subjects: Q Science > Q Science (General) > Q325.5 Machine learning
T Technology > TJ Mechanical engineering and machinery
T Technology > TJ Mechanical engineering and machinery > TJ163.12 Mechatronics
Divisions: Faculty of Engineering and Information Technology > Department of Mechatronics Engineering
Depositing User: Faisal Ifzaldi
Date Deposited: 24 Dec 2021 17:37
Last Modified: 24 Dec 2021 17:37
URI: http://repository.sgu.ac.id/id/eprint/2230

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