A Web-based Image Recognition System for Detecting Harumanis Mangoes

Harumanis mango cultivar is special to Perlis (north state of Malaysia) and has been declared in the national agenda as a special fruit. For those who are not acquainted with aromatic mango, it is difficult to tell the distinction between Harumanis and the others . By using image recognition, people...

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Formato:	article
Lenguaje:	EN
Publicado:	Faculty of Computer and Mathematical Sciences, Universiti Teknologi MARA Perlis 2020
Materias:	Probabilities. Mathematical statistics QA273-280 Technology T Technology (General) T1-995
Acceso en línea:	https://doaj.org/article/d5f4fefaf3284cd2af852a0ba56ca7a3
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spelling	oai:doaj.org-article:d5f4fefaf3284cd2af852a0ba56ca7a32021-11-06T02:23:05ZA Web-based Image Recognition System for Detecting Harumanis Mangoes 2600-8793https://doaj.org/article/d5f4fefaf3284cd2af852a0ba56ca7a32020-10-01T00:00:00Zhttp://repeater.my/index.php/jcrinn/article/view/153https://doaj.org/toc/2600-8793Harumanis mango cultivar is special to Perlis (north state of Malaysia) and has been declared in the national agenda as a special fruit. For those who are not acquainted with aromatic mango, it is difficult to tell the distinction between Harumanis and the others . By using image recognition, people can identify Harumanis feature details by image recognition technique where algorithm is applied to recognize the mango. Convolutional neural networks method is a suitable technique for the creation of a multi - fruit in re al - time classification sorter with the camera and for the detection of moving fruit. Furthermore, the accuracy of the image classification can be improved by increasing the number of datasets, the distance of images from the camera, and the labelling proce ss. This project used Mobile Net architecture model because it consumes less computational power and it can also provide efficiency of the accuracy. A w eb - based i mage r ecognition s ystem for d etecting Harumanis m angoes was developed and known as CamPauh to recognize four classes of mango which are H arumanis, apple mango, other type s of mango es and not mango. CamPauh ca n identify different type of mangoes and the result was stored into the database and appeared on the websit e. E valuation on the accuracy was conducted discussed to support users ’ satisfaction in identifying the correct mango type.Faculty of Computer and Mathematical Sciences, Universiti Teknologi MARA PerlisarticleProbabilities. Mathematical statisticsQA273-280TechnologyTTechnology (General)T1-995ENJournal of Computing Research and Innovation, Vol 5, Iss 4 (2020)
institution	DOAJ
collection	DOAJ
language	EN
topic	Probabilities. Mathematical statistics QA273-280 Technology T Technology (General) T1-995
spellingShingle	Probabilities. Mathematical statistics QA273-280 Technology T Technology (General) T1-995 A Web-based Image Recognition System for Detecting Harumanis Mangoes
description	Harumanis mango cultivar is special to Perlis (north state of Malaysia) and has been declared in the national agenda as a special fruit. For those who are not acquainted with aromatic mango, it is difficult to tell the distinction between Harumanis and the others . By using image recognition, people can identify Harumanis feature details by image recognition technique where algorithm is applied to recognize the mango. Convolutional neural networks method is a suitable technique for the creation of a multi - fruit in re al - time classification sorter with the camera and for the detection of moving fruit. Furthermore, the accuracy of the image classification can be improved by increasing the number of datasets, the distance of images from the camera, and the labelling proce ss. This project used Mobile Net architecture model because it consumes less computational power and it can also provide efficiency of the accuracy. A w eb - based i mage r ecognition s ystem for d etecting Harumanis m angoes was developed and known as CamPauh to recognize four classes of mango which are H arumanis, apple mango, other type s of mango es and not mango. CamPauh ca n identify different type of mangoes and the result was stored into the database and appeared on the websit e. E valuation on the accuracy was conducted discussed to support users ’ satisfaction in identifying the correct mango type.
format	article
title	A Web-based Image Recognition System for Detecting Harumanis Mangoes
title_short	A Web-based Image Recognition System for Detecting Harumanis Mangoes
title_full	A Web-based Image Recognition System for Detecting Harumanis Mangoes
title_fullStr	A Web-based Image Recognition System for Detecting Harumanis Mangoes
title_full_unstemmed	A Web-based Image Recognition System for Detecting Harumanis Mangoes
title_sort	web-based image recognition system for detecting harumanis mangoes
publisher	Faculty of Computer and Mathematical Sciences, Universiti Teknologi MARA Perlis
publishDate	2020
url	https://doaj.org/article/d5f4fefaf3284cd2af852a0ba56ca7a3
_version_	1718444011295866880

A Web-based Image Recognition System for Detecting Harumanis Mangoes

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