Citation

Afiq Razali, Norazrai Daniel and Mohd Zarifie Hashim, Nik and Amir Che Hamid, Muhammad Nur and Dwi Sulistiyo, Mahmud and Abd Rahman, Noor Ziela and Mohd Yusoff, Salizawati (2025) Exploring Multi-Angle Imaging for Food Safety and Security Through Computer Vision. In: 2025 Multimedia University Engineering Conference, MECON 2025, 21 July 2025 - 23 July 2025, Cyberjaya, Malaysia.

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Abstract

Food safety and security represents a worldwide essential problem which needs advanced monitoring systems and quality assessment methods. The research investigates multi-angle imaging for food observation through computer vision methods to enhance both detection accuracy and reliability. The traditional food inspection methods conduct assessments from a single perspective which fail to detect vital defects that become invisible during viewing angles. The method provides better food property understanding through multipleangle photography which enables precise identification of spoilage and foreign objects and texture modifications. The multi-angle imaging approach improves visibility through reduced occlusions and better feature extraction and surface detail detection which single-angle observations would miss. The proposed system combines machine learning models with computer vision algorithms to analyze multi-angle images which enhances the robustness of food quality assessment. Experimental data shows that different viewing perspectives boost classification accuracy while decreasing detection errors and enhancing real-time monitoring reliability. The research demonstrates that multi-angle imaging creates an automated system which provides detailed food safety evaluations. The research employs AI technologies to support global food security initiatives while improving food quality management standards and protecting consumer safety.

Item Type:	Conference or Workshop Item (Paper)
Uncontrolled Keywords:	Artificial intelligence, computer vision
Subjects:	Q Science > QA Mathematics > QA71-90 Instruments and machines > QA75.5-76.95 Electronic computers. Computer science
Divisions:	Faculty of Engineering and Technology (FET)
Depositing User:	Ms Rosnani Abd Wahab
Date Deposited:	18 Mar 2026 08:02
Last Modified:	19 Mar 2026 00:56
URII:	http://shdl.mmu.edu.my/id/eprint/15571

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