Automated Detection and Rectification of Defects in Fluid-Based Packaging using Machine Vision

Katyal, Nipun; Kumar, M. Sandeep; Deshmukh, Prathamesh; Nersisson, Ruban

doi:10.1109/iscas.2019.8702568

Cited by 3 publications

(2 citation statements)

References 9 publications

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“…(2020) Crop Detecting DWT, PCA, PNN accuracy = 86.48% Pujari et al. (2013) Fluid Monitoring CNN accuracy = 99.76% Katyal et al. (2019) General Packaging OCV, OCR, FCN, MSER accuracy > 97.1% De Sousa Ribeiro et al.…”

Section: Machine Learning Approachesmentioning

confidence: 99%

Deep learning and machine vision for food processing: A survey

Zhu

Spachos

Pensini

et al. 2021

Current Research in Food Science

156

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The quality and safety of food is an important issue to the whole society, since it is at the basis of human health, social development and stability. Ensuring food quality and safety is a complex process, and all stages of food processing must be considered, from cultivating, harvesting and storage to preparation and consumption. However, these processes are often labour-intensive. Nowadays, the development of machine vision can greatly assist researchers and industries in improving the efficiency of food processing. As a result, machine vision has been widely used in all aspects of food processing. At the same time, image processing is an important component of machine vision. Image processing can take advantage of machine learning and deep learning models to effectively identify the type and quality of food. Subsequently, follow-up design in the machine vision system can address tasks such as food grading, detecting locations of defective spots or foreign objects, and removing impurities. In this paper, we provide an overview on the traditional machine learning and deep learning methods, as well as the machine vision techniques that can be applied to the field of food processing. We present the current approaches and challenges, and the future trends.

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Section: Machine Learning Approachesmentioning

confidence: 99%

Deep learning and machine vision for food processing: A survey

Zhu

Spachos

Pensini

et al. 2021

Current Research in Food Science

156

View full text Add to dashboard Cite

show abstract

“…However, existing OCR systems can not perform effectively in real-world expiry date recognition scenarios, with high variability, different fonts/angles, complicated designs with rich colours/textures, blurred characters poor lighting conditions in food manufacturing/ retailer sites. Deep neural networks have been recently used as a means to tackle such problems [68,69].…”

Section: The Fcn-crnn Approach For Expiry Date Recognitionmentioning

confidence: 99%

AI-enabled Efficient and Safe Food Supply Chain

Kollia¹,

Stevenson²,

Kollias³

2021

Preprint

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This paper provides a review of an emerging field in the food processing sector, referring to efficient and safe food supply chains, 'from farm to fork', as enabled by Artificial Intelligence (AI). Recent advances in machine and deep learning are used for effective food production, energy management and food labeling. Appropriate deep neural architectures are adopted and used for this purpose, including Fully Convolutional Networks, Long Short-Term Memories and Recurrent Neural Networks, Auto-Encoders and Attention mechanisms, Latent Variable extraction and clustering, as well as Domain Adaptation. Three experimental studies are presented, illustrating the ability of these AI methodologies to produce state-of-the-art performance in the whole food supply chain. In particular, these concern: (i) predicting plant growth and tomato yield in greenhouses, thus matching food production to market needs and reducing food waste or food unavailability; (ii) optimizing energy consumption across large networks of food retail refrigeration systems, through optimal selection of systems that can get shutdown and through prediction of the respective food de-freezing times, during peaks of power demand load; (iii) optical recognition and verification of food consumption expiry date in automatic inspection of retail packaged food, thus ensuring safety of food and people's health.

show abstract

AI-Enabled Efficient and Safe Food Supply Chain

2021

View full text Add to dashboard Cite

This paper provides a review of an emerging field in the food processing sector, referring to efficient and safe food supply chains, ’from farm to fork’, as enabled by Artificial Intelligence (AI). The field is of great significance from economic, food safety and public health points of views. The paper focuses on effective food production, food maintenance energy management and food retail packaging labeling control, using recent advances in machine learning. Appropriate deep neural architectures are adopted and used for this purpose, including Fully Convolutional Networks, Long Short-Term Memories and Recurrent Neural Networks, Auto-Encoders and Attention mechanisms, Latent Variable extraction and clustering, as well as Domain Adaptation. Three experimental studies are presented, illustrating the ability of these AI methodologies to produce state-of-the-art performance in the whole food supply chain. In particular, these concern: (i) predicting plant growth and tomato yield in greenhouses, thus matching food production to market needs and reducing food waste or food unavailability; (ii) optimizing energy consumption across large networks of food retail refrigeration systems, through optimal selection of systems that can be shut-down and through prediction of the respective food de-freezing times, during peaks of power demand load; (iii) optical recognition and verification of food consumption expiry date in automatic inspection of retail packaged food, thus ensuring safety of food and people’s health.

show abstract

Automated Detection and Rectification of Defects in Fluid-Based Packaging using Machine Vision

Cited by 3 publications

References 9 publications

Deep learning and machine vision for food processing: A survey

Deep learning and machine vision for food processing: A survey

AI-enabled Efficient and Safe Food Supply Chain

AI-Enabled Efficient and Safe Food Supply Chain

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