Current progress in the utilization of smartphone-based imaging for quality assessment of food products: a review

Abstract

The cell phone has been merely used for image acquisition and transmission in the last decades. Owing to the recent technological progress, its new generation, i.e., the smartphone, draws remarkable attention to food quality assessment with versatile applications. Smartphones possess high-resolution cameras, enabling them to be used instead of digital cameras in the computer vision system. Furthermore, their programmability and portability have recently encouraged researchers to introduce smartphone-based image processing in food analytical studies. This promising approach has advantages such as high sensing capability, being user friendly, and cost-effective over the conventional method, and therefore might be considered an emerging nondestructive technique for quality control purposes. However, there is a great effort to tackle implementation, calibration, as well as industrialization issues. In this context, this review aims to highlight the most recent studies of smartphone-based imaging systems in various food systems such as dairy, meat, fruit, and vegetables. Besides, the existing challenges and future trends for applying smartphones in food quality control are discussed. Although moving the computer vision systems toward a portable tool like a smartphone improves its versatility, more research works are needed to resolve its set-up weakness and limitations.

Keywords:

• Smartphone
• computer vision
• image processing
• food products

Acknowledgements

The authors are grateful to the Doctoral School of Food Sciences, Szent István University, for their supports.

Disclosure statement

The authors declare no conflict of interest.

Additional information

Funding

This work was supported by the European Union and co-financed by the European Social Fund under grant agreement no. EFOP-3.6.3-VEKOP-16-2017-00005. The authors are also grateful for the NDRI Fund's support (grant agreement no. 2017-1.3.1-VKE-2017-00018).