Detection of harmful substances in underarm product using optical character recognition and support vector machine / Nur Hidayah Abdul Ghani

Products for the underarm area which includes deodorant and antiperspirant are vital for maintaining personal hygiene, however some people are worried about how the product itself can affect their health and general wellbeing due to unfamiliar ingredients name on the label. Existing applications tha...

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Main Author:	Abdul Ghani, Nur Hidayah
Format:	Thesis
Language:	English
Published:	2023
Subjects:	TP Chemical technology
Online Access:	https://ir.uitm.edu.my/id/eprint/89016/1/89016.pdf
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id	my-uitm-ir.89016
record_format	uketd_dc
spelling	my-uitm-ir.890162024-03-19T07:07:38Z Detection of harmful substances in underarm product using optical character recognition and support vector machine / Nur Hidayah Abdul Ghani 2023 Abdul Ghani, Nur Hidayah TP Chemical technology Products for the underarm area which includes deodorant and antiperspirant are vital for maintaining personal hygiene, however some people are worried about how the product itself can affect their health and general wellbeing due to unfamiliar ingredients name on the label. Existing applications that are available for consumer to check safeties of a product frequently require users to create an account, include advertisements or provide unhelpful result. Thus, people manually search up each ingredient of the product using any search engine which is time-consuming. Hence, this study aims to develop a user-friendly system that can quickly and accurately identify harsh chemical substances in underarm products. The system uses Optical Character Recognition (OCR) and Support Vector Machine (SVM) to extract ingredients name and classify the product respectively. This study reveals how well the system classifies underarm product and enable users to make a great choice about the safety of the product. This is due to the accuracy obtained from classifying 120 testing data using Support Vector Machine classifier and achieved 93.4%. In conclusion, the suggested technique offers a potential way to get over the constraints of existing applications, then giving the consumer a quick and reliable way to choose a safe underarm product for everyday use. As for future work, the system database might be expanded with list of chemical compounds in order to detect more harmful substances in the future. Next, various methods of machine learning and OCR tools could be evaluated for improved performance and classification accuracy and text detection respectively in the future research for further improvement 2023 Thesis https://ir.uitm.edu.my/id/eprint/89016/ https://ir.uitm.edu.my/id/eprint/89016/1/89016.pdf text en public degree Universiti Teknologi MARA, Melaka College of Computing, Informatics and Mathematics
institution	Universiti Teknologi MARA
collection	UiTM Institutional Repository
language	English
topic	TP Chemical technology
spellingShingle	TP Chemical technology Abdul Ghani, Nur Hidayah Detection of harmful substances in underarm product using optical character recognition and support vector machine / Nur Hidayah Abdul Ghani
description	Products for the underarm area which includes deodorant and antiperspirant are vital for maintaining personal hygiene, however some people are worried about how the product itself can affect their health and general wellbeing due to unfamiliar ingredients name on the label. Existing applications that are available for consumer to check safeties of a product frequently require users to create an account, include advertisements or provide unhelpful result. Thus, people manually search up each ingredient of the product using any search engine which is time-consuming. Hence, this study aims to develop a user-friendly system that can quickly and accurately identify harsh chemical substances in underarm products. The system uses Optical Character Recognition (OCR) and Support Vector Machine (SVM) to extract ingredients name and classify the product respectively. This study reveals how well the system classifies underarm product and enable users to make a great choice about the safety of the product. This is due to the accuracy obtained from classifying 120 testing data using Support Vector Machine classifier and achieved 93.4%. In conclusion, the suggested technique offers a potential way to get over the constraints of existing applications, then giving the consumer a quick and reliable way to choose a safe underarm product for everyday use. As for future work, the system database might be expanded with list of chemical compounds in order to detect more harmful substances in the future. Next, various methods of machine learning and OCR tools could be evaluated for improved performance and classification accuracy and text detection respectively in the future research for further improvement
format	Thesis
qualification_level	Bachelor degree
author	Abdul Ghani, Nur Hidayah
author_facet	Abdul Ghani, Nur Hidayah
author_sort	Abdul Ghani, Nur Hidayah
title	Detection of harmful substances in underarm product using optical character recognition and support vector machine / Nur Hidayah Abdul Ghani
title_short	Detection of harmful substances in underarm product using optical character recognition and support vector machine / Nur Hidayah Abdul Ghani
title_full	Detection of harmful substances in underarm product using optical character recognition and support vector machine / Nur Hidayah Abdul Ghani
title_fullStr	Detection of harmful substances in underarm product using optical character recognition and support vector machine / Nur Hidayah Abdul Ghani
title_full_unstemmed	Detection of harmful substances in underarm product using optical character recognition and support vector machine / Nur Hidayah Abdul Ghani
title_sort	detection of harmful substances in underarm product using optical character recognition and support vector machine / nur hidayah abdul ghani
granting_institution	Universiti Teknologi MARA, Melaka
granting_department	College of Computing, Informatics and Mathematics
publishDate	2023
url	https://ir.uitm.edu.my/id/eprint/89016/1/89016.pdf
_version_	1794192188294299648

Detection of harmful substances in underarm product using optical character recognition and support vector machine / Nur Hidayah Abdul Ghani

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