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RECOGNITION OF NUTRIENTS FOR DIETARY ASSESSMENTS USING MOBILE IMAGES

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dc.contributor.authorNik Muhammad Afiq bin Nik Sofizanen_US
dc.date.accessioned2023-05-03T17:12:17Z
dc.date.available2023-05-03T17:12:17Z
dc.date.issued2020-02
dc.descriptionFYP 2 SEM 2 2019/2020en_US
dc.description.abstractFood consumption are very important in maintaining a healthy lifestyle. More people are becoming aware of their health problems hence looking into having a healthier diet. For that, this thesis plans on providing a basic support regarding Optical Character Recognition (OCR) on food products. This is for the consumers to easily navigate through food consumptions and daily food intake. There were not many researches on providing an OCR technology on food products. However, some have proven to working on the direction to generate and produced an application recognise characters on food product to be tabulated into an application. Moreover, template matching techniques have proven to be reliable in many different areas of OCR technology. Many researchers have developed different techniques for OCR. This paper uses template matching technique with minimal machine learning to acknowledge the problem hence creating a basis for future development.en_US
dc.identifier.urihttps://irepository.uniten.edu.my/handle/123456789/21541
dc.language.isoenen_US
dc.subjectOCRen_US
dc.subjectTemplate Matchingen_US
dc.titleRECOGNITION OF NUTRIENTS FOR DIETARY ASSESSMENTS USING MOBILE IMAGESen_US
dspace.entity.typePublication
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