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Starfruit ripeness classification system based on image processing technique / Wan Muhammad Akram Wan Hasan

Starfruit ripeness classification system based on image processing is a system to identify the ripeness of starfruit whether the starfruit is unripe, ripe or overripe condition. This is the automation system of identifying the ripeness of starfruit replacing the conventional starfruit inspection. Cu...

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Main Author: Wan Hasan, Wan Muhammad Akram
Format: Student Project
Language:English
Published: 2018
Subjects:
Philosophy. Theory. Classification. Methodology
Industrial research. Research and development
Industrial engineering. Management engineering
Probability theory
Work measurement. Methods engineering
Online Access:http://ir.uitm.edu.my/id/eprint/38103/1/38103.pdf
http://ir.uitm.edu.my/id/eprint/38103/
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spelling my.uitm.ir.381032020-12-09T09:24:44Z http://ir.uitm.edu.my/id/eprint/38103/ Starfruit ripeness classification system based on image processing technique / Wan Muhammad Akram Wan Hasan Wan Hasan, Wan Muhammad Akram Philosophy. Theory. Classification. Methodology Industrial research. Research and development Industrial engineering. Management engineering Probability theory Work measurement. Methods engineering Starfruit ripeness classification system based on image processing is a system to identify the ripeness of starfruit whether the starfruit is unripe, ripe or overripe condition. This is the automation system of identifying the ripeness of starfruit replacing the conventional starfruit inspection. Currently the inspection of conventional system used by farmer to inspect the ripeness is time consuming and the accuracy of this operation cannot be guaranteed. This system is suitable used in agriculture to inspect the ripeness of fruit. The main objective of this project is to classify the ripeness of starfruit by using Artificial Neural Network based on image processing technique which for this project RGB counter value component will be used. For this project the samples of different level of ripeness were collected, image processing technique and image classification by using neural network were used. Starfruit images were captured using Canon EOS 7D with 18 megapixel. 180 samples were used as training samples for neural network. After training samples another 75 samples is used for testing in order to identify the ripeness of starfruit and to calculate the accuracy of the process. At the end result of the project about 73 samples of starfruit can classified correctly and the accuracy achieve for this project is 97.33%. This shows that the classification of starfruit based on image processing technique using artificial neural network can be used to classified ripeness. 2018-01 Student Project NonPeerReviewed text en http://ir.uitm.edu.my/id/eprint/38103/1/38103.pdf Wan Hasan, Wan Muhammad Akram (2018) Starfruit ripeness classification system based on image processing technique / Wan Muhammad Akram Wan Hasan. [Student Project] (Unpublished)
institution Universiti Teknologi Mara
building Tun Abdul Razak Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Mara
content_source UiTM Institutional Repository
url_provider http://ir.uitm.edu.my/
language English
topic Philosophy. Theory. Classification. Methodology
Industrial research. Research and development
Industrial engineering. Management engineering
Probability theory
Work measurement. Methods engineering
spellingShingle Philosophy. Theory. Classification. Methodology
Industrial research. Research and development
Industrial engineering. Management engineering
Probability theory
Work measurement. Methods engineering
Wan Hasan, Wan Muhammad Akram
Starfruit ripeness classification system based on image processing technique / Wan Muhammad Akram Wan Hasan
description Starfruit ripeness classification system based on image processing is a system to identify the ripeness of starfruit whether the starfruit is unripe, ripe or overripe condition. This is the automation system of identifying the ripeness of starfruit replacing the conventional starfruit inspection. Currently the inspection of conventional system used by farmer to inspect the ripeness is time consuming and the accuracy of this operation cannot be guaranteed. This system is suitable used in agriculture to inspect the ripeness of fruit. The main objective of this project is to classify the ripeness of starfruit by using Artificial Neural Network based on image processing technique which for this project RGB counter value component will be used. For this project the samples of different level of ripeness were collected, image processing technique and image classification by using neural network were used. Starfruit images were captured using Canon EOS 7D with 18 megapixel. 180 samples were used as training samples for neural network. After training samples another 75 samples is used for testing in order to identify the ripeness of starfruit and to calculate the accuracy of the process. At the end result of the project about 73 samples of starfruit can classified correctly and the accuracy achieve for this project is 97.33%. This shows that the classification of starfruit based on image processing technique using artificial neural network can be used to classified ripeness.
format Student Project
author Wan Hasan, Wan Muhammad Akram
author_facet Wan Hasan, Wan Muhammad Akram
author_sort Wan Hasan, Wan Muhammad Akram
title Starfruit ripeness classification system based on image processing technique / Wan Muhammad Akram Wan Hasan
title_short Starfruit ripeness classification system based on image processing technique / Wan Muhammad Akram Wan Hasan
title_full Starfruit ripeness classification system based on image processing technique / Wan Muhammad Akram Wan Hasan
title_fullStr Starfruit ripeness classification system based on image processing technique / Wan Muhammad Akram Wan Hasan
title_full_unstemmed Starfruit ripeness classification system based on image processing technique / Wan Muhammad Akram Wan Hasan
title_sort starfruit ripeness classification system based on image processing technique / wan muhammad akram wan hasan
publishDate 2018
url http://ir.uitm.edu.my/id/eprint/38103/1/38103.pdf
http://ir.uitm.edu.my/id/eprint/38103/
_version_ 1687396682828873728
score 13.211869

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