Identification of foreign materials in food using passive terahertz imaging and deep learning
Food contamination is a major concern in the food industry as it can incur serious health risks to the consumers. For instance, perforation can occur when sharp objects are swallowed. Physical contaminants are the most noticeable type of food contamination and preventive measures can be put in place...
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sg-ntu-dr.10356-1588922023-03-04T20:08:27Z Identification of foreign materials in food using passive terahertz imaging and deep learning Ong, Eng Zia Cai Yiyu School of Mechanical and Aerospace Engineering MYYCai@ntu.edu.sg Engineering::Computer science and engineering::Computing methodologies::Image processing and computer vision Engineering::Mechanical engineering Food contamination is a major concern in the food industry as it can incur serious health risks to the consumers. For instance, perforation can occur when sharp objects are swallowed. Physical contaminants are the most noticeable type of food contamination and preventive measures can be put in place to ensure that the food products that are sold to the end consumers are free of foreign bodies. Some of the commonly found physical contaminants in food include glass, plastics, stones and metals. Most of the food manufacturers uses the conventional metal detector and X-ray imaging to filter out the contaminated food. However, there are limitations to the aforementioned machines, leading to complaints still being filed by the consumers regarding foreign materials being found even though measures already put in place to prevent such scenarios from happening. Not only does such experience cause psychological traumatism and danger to the consumer, business reputation would also be negatively affected. As such, terahertz imaging is proposed to aid the scanning of the finished food products, capturing foreign materials that the conventional scanning methods are not capable of. Application of passive terahertz imaging with continuous-wave to scan the food products is investigated in this project. The identification of foreign materials from the images obtained through passive terahertz imaging is automated through the application of deep learning. Results show acceptable accuracies for foreign materials detection. The limitations of the proposed method and further works that can be done for this method are also discussed in this report for future development to integrate in the industry. Bachelor of Engineering (Mechanical Engineering) 2022-06-06T06:35:21Z 2022-06-06T06:35:21Z 2022 Final Year Project (FYP) Ong, E. Z. (2022). Identification of foreign materials in food using passive terahertz imaging and deep learning. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/158892 https://hdl.handle.net/10356/158892 en C005 application/pdf Nanyang Technological University |
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Engineering::Computer science and engineering::Computing methodologies::Image processing and computer vision Engineering::Mechanical engineering Ong, Eng Zia Identification of foreign materials in food using passive terahertz imaging and deep learning |
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Food contamination is a major concern in the food industry as it can incur serious health risks to the consumers. For instance, perforation can occur when sharp objects are swallowed. Physical contaminants are the most noticeable type of food contamination and preventive measures can be put in place to ensure that the food products that are sold to the end consumers are free of foreign bodies. Some of the commonly found physical contaminants in food include glass, plastics, stones and metals. Most of the food manufacturers uses the conventional metal detector and X-ray imaging to filter out the contaminated food. However, there are limitations to the aforementioned machines, leading to complaints still being filed by the consumers regarding foreign materials being found even though measures already put in place to prevent such scenarios from happening. Not only does such experience cause psychological traumatism and danger to the consumer, business reputation would also be negatively affected. As such, terahertz imaging is proposed to aid the scanning of the finished food products, capturing foreign materials that the conventional scanning methods are not capable of. Application of passive terahertz imaging with continuous-wave to scan the food products is investigated in this project. The identification of foreign materials from the images obtained through passive terahertz imaging is automated through the application of deep learning. Results show acceptable accuracies for foreign materials detection. The limitations of the proposed method and further works that can be done for this method are also discussed in this report for future development to integrate in the industry. |
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Cai Yiyu |
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Cai Yiyu Ong, Eng Zia |
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Final Year Project |
author |
Ong, Eng Zia |
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Ong, Eng Zia |
title |
Identification of foreign materials in food using passive terahertz imaging and deep learning |
title_short |
Identification of foreign materials in food using passive terahertz imaging and deep learning |
title_full |
Identification of foreign materials in food using passive terahertz imaging and deep learning |
title_fullStr |
Identification of foreign materials in food using passive terahertz imaging and deep learning |
title_full_unstemmed |
Identification of foreign materials in food using passive terahertz imaging and deep learning |
title_sort |
identification of foreign materials in food using passive terahertz imaging and deep learning |
publisher |
Nanyang Technological University |
publishDate |
2022 |
url |
https://hdl.handle.net/10356/158892 |
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1759855994166312960 |