A web-based image recognition system for detecting harumanis mangoes / Mohamad Shahmil Saari, Romiza Md Nor and Huzaifah A Hamid

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...

Full description

Saved in:
Bibliographic Details
Main Authors: Saari, Mohamad Shahmil, Md Nor, Romiza, Huzaifah, A Hamid
Format: Article
Language:en
Published: UiTM Cawangan Perlis 2020
Subjects:
Online Access:https://ir.uitm.edu.my/id/eprint/43369/1/43369.pdf
https://ir.uitm.edu.my/id/eprint/43369/
https://crinn.conferencehunter.com/
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1833067240784658432
author Saari, Mohamad Shahmil
Md Nor, Romiza
Huzaifah, A Hamid
author_facet Saari, Mohamad Shahmil
Md Nor, Romiza
Huzaifah, A Hamid
author_sort Saari, Mohamad Shahmil
building Tun Abdul Razak Library
collection Institutional Repository
content_provider Universiti Teknologi Mara
content_source UiTM Institutional Repository
continent Asia
country Malaysia
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 real-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 process. This project used Mobile Net architecture model because it consumes less computational power and it can also provide efficiency of the accuracy. A web-based image recognition system for detecting Harumanis mangoes was developed and known as CamPauh to recognize four classes of mango which are Harumanis, apple mango, other types of mangoes and not mango. CamPauh can identify different type of mangoes and the result was stored into the database and appeared on the website. Evaluation on the accuracy was conducted discussed to support users’ satisfaction in identifying the correct mango type.
format Article
id my.uitm.ir-43369
institution Universiti Teknologi Mara
language en
publishDate 2020
publisher UiTM Cawangan Perlis
record_format eprints
spelling my.uitm.ir-433692021-05-11T00:25:44Z https://ir.uitm.edu.my/id/eprint/43369/ A web-based image recognition system for detecting harumanis mangoes / Mohamad Shahmil Saari, Romiza Md Nor and Huzaifah A Hamid jcrinn Saari, Mohamad Shahmil Md Nor, Romiza Huzaifah, A Hamid Web-based user interfaces. User interfaces (Computer systems) Fruit and fruit culture 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 real-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 process. This project used Mobile Net architecture model because it consumes less computational power and it can also provide efficiency of the accuracy. A web-based image recognition system for detecting Harumanis mangoes was developed and known as CamPauh to recognize four classes of mango which are Harumanis, apple mango, other types of mangoes and not mango. CamPauh can identify different type of mangoes and the result was stored into the database and appeared on the website. Evaluation on the accuracy was conducted discussed to support users’ satisfaction in identifying the correct mango type. UiTM Cawangan Perlis 2020 Article PeerReviewed text en https://ir.uitm.edu.my/id/eprint/43369/1/43369.pdf A web-based image recognition system for detecting harumanis mangoes / Mohamad Shahmil Saari, Romiza Md Nor and Huzaifah A Hamid. (2020) Journal of Computing Research and Innovation (JCRINN) <https://ir.uitm.edu.my/view/publication/Journal_of_Computing_Research_and_Innovation_=28JCRINN=29/>, 5 (4). pp. 48-53. ISSN 2600-8793 https://crinn.conferencehunter.com/
spellingShingle Web-based user interfaces. User interfaces (Computer systems)
Fruit and fruit culture
Saari, Mohamad Shahmil
Md Nor, Romiza
Huzaifah, A Hamid
A web-based image recognition system for detecting harumanis mangoes / Mohamad Shahmil Saari, Romiza Md Nor and Huzaifah A Hamid
title A web-based image recognition system for detecting harumanis mangoes / Mohamad Shahmil Saari, Romiza Md Nor and Huzaifah A Hamid
title_full A web-based image recognition system for detecting harumanis mangoes / Mohamad Shahmil Saari, Romiza Md Nor and Huzaifah A Hamid
title_fullStr A web-based image recognition system for detecting harumanis mangoes / Mohamad Shahmil Saari, Romiza Md Nor and Huzaifah A Hamid
title_full_unstemmed A web-based image recognition system for detecting harumanis mangoes / Mohamad Shahmil Saari, Romiza Md Nor and Huzaifah A Hamid
title_short A web-based image recognition system for detecting harumanis mangoes / Mohamad Shahmil Saari, Romiza Md Nor and Huzaifah A Hamid
title_sort web-based image recognition system for detecting harumanis mangoes / mohamad shahmil saari, romiza md nor and huzaifah a hamid
topic Web-based user interfaces. User interfaces (Computer systems)
Fruit and fruit culture
url https://ir.uitm.edu.my/id/eprint/43369/1/43369.pdf
https://ir.uitm.edu.my/id/eprint/43369/
https://crinn.conferencehunter.com/
url_provider http://ir.uitm.edu.my/