Abstract
The paper reports design and fabrication of a low-cost solution for monitoring food quality. Owing to its widespread popularity worldwide for regular food item, potato has been chosen as an object to be classified according to quality features such as size, shape, surface texture, and color. The system design includes classifier design for potato detection, ROI segregation, and analysis of certain statistical parameter. For the present study, potatoes have been classified as grade-1 and grade-2. Grade-1 potatoes are those which have to be retained while grade-2 potatoes have to be discarded. ARM-based embedded platform has been chosen for implementation. The system performance meets the required specifications.
This is a preview of subscription content, log in via an institution.
References
Miertuš, Stanislav, Jaroslav Katrlı́k, Andrea Pizzariello, Miroslav Stred’anský, Juraj Švitel, and Jozef Švorc. “Amperometric biosensors based on solid binding matrices applied in food quality monitoring.” Biosensors and Bioelectronics 13, no. 7 (1998): 911–923.
Rodríguez-Lázaro, D., Lombard, B., Smith, H., Rzezutka, A., D’Agostino, M., Helmuth, R., Schroeter, A., Malorny, B., Miko, A., Guerra, B. and Davison, J., 2007. Trends in analytical methodology in food safety and quality: monitoring microorganisms and genetically modified organisms. Trends in food science & technology, 18(6), pp. 306–319.
Tewari, G. and Juneja, V. eds., 2008. Advances in thermal and non-thermal food preservation. John Wiley & Sons.
Fellows, P.J., 2009. Food processing technology: principles and practice. Elsevier.
Sharma, P., Gupta, M.K., Mondal, A.K. and Kaundal, V., 2017. HAAR like Feature-Based Car Key Detection Using Cascade Classifier. In Proceeding of International Conference on Intelligent Communication, Control and Devices (pp. 689–694). Springer Singapore.
Wen, X., Shao, L., Xue, Y. and Fang, W., 2015. A rapid learning algorithm for vehicle classification. Information Sciences, 295, pp. 395–406.
Seo, N., 2008. Tutorial: OpenCV haartraining (rapid object detection with a cascade of boosted classifiers based on haar-like features). available on.
Elmer, P., Lupp, A., Sprenger, S., Thaler, R. and Uhl, A., 2015, June. Exploring compression impact on face detection using haar-like features. In Scandinavian Conference on Image Analysis (pp. 53–64). Springer International Publishing.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2018 Springer Nature Singapore Pte Ltd.
About this paper
Cite this paper
Agrahari, A., Pande, R., Sharma, P., Kaundal, V. (2018). Design of a Low-Cost Potato Quality Monitoring System. In: Singh, R., Choudhury, S., Gehlot, A. (eds) Intelligent Communication, Control and Devices. Advances in Intelligent Systems and Computing, vol 624. Springer, Singapore. https://doi.org/10.1007/978-981-10-5903-2_122
Download citation
DOI: https://doi.org/10.1007/978-981-10-5903-2_122
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-10-5902-5
Online ISBN: 978-981-10-5903-2
eBook Packages: EngineeringEngineering (R0)