Segmentation of Dishes for Customer Service Automation in a Self-service Canteen

• Autorzy: Kryjak T. , Krol D. , Gorgon M.

Identyfikatory

DOI

10.1515/ipc-2015-0030

• Języki publikacji: EN

Abstrakty

EN

The article describes research on dishes segmentation for the purposes of customer service process automation in a self-service canteen. The project assumptions and a prototype test stand are presented. The developed empty workspace detection and tray position determination algorithms are discussed. Finally, the chosen dishes segmentation algorithm is described and justified.

Słowa kluczowe

EN

RFID; image processing; video surveillance

• Wydawca: Instytut Telekomunikacji i Informatyki Uniwersytetu Technologiczno-Przyrodniczego w Bydgoszczy
• Czasopismo: Image Processing & Communications
• Rocznik: 2015
• Tom: Vol. 20, no. 2
• Strony: 5--16
• Opis fizyczny: Bibliogr. 9 poz., rys., tab.

Twórcy

autor

Kryjak T.

• AGH University of Science and Technology, al. Mickiewicza 30, 30-059 Krakow

autor

Krol D.

• AGH University of Science and Technology, al. Mickiewicza 30, 30-059 Krakow

autor

Gorgon M.

• AGH University of Science and Technology, al. Mickiewicza 30, 30-059 Krakow

Bibliografia

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• [2] -, (2015). Recognition Technology, http://www.sri.com/engage/products-solutions/food-recognition-technology (last access: May 2015)
• [3] Bettadapura, V., Thomaz, E., Parnami, A., Abowd, G.D., Essa, I. (2015, January). Leveraging Context to Support Automated Food Recognition in Restaurants. In Applications of Computer Vision (WACV), 2015 IEEE Winter Conference on (pp. 580-587). IEEE
• [4] Bouwmans, T. (2014). Traditional and recent approaches in background modeling for foreground detection: An overview. Computer Science Review, 11, 31-66
• [5] Bouwmans, T., Porikli, F., Höferlin, B., Vacavant, A. (Eds.). (2014). Background Modeling and Foreground Detection for Video Surveillance. CRC Press
• [6] He, H., Kong, F., Tan, J. (2015). DietCam: Multi-View Food Recognition Using a Multi-Kernel SVM. Biomedical and Health Informatics, IEEE Journal of, (99), 1-1
• [7] Kawano, Y., Yanai, K. (2013, June). Real-time mobile food recognition system. In Computer Vision and Pattern Recognition Workshops (CVPRW), 2013 IEEE Conference on (pp. 1-7). IEEE
• [8] Kryjak, T., Krol, D. (2015, September). Shape and colour recognition of dishes for the purpose of customer service process automation in a self-service canteen. In Computer Science and Information Systems (FedCSIS), 2015 Federated Conference on (pp. 799-808). IEEE
• [9] Zhu, F., Bosch, M., Khanna, N., Boushey, C.J., Delp, E.J. (2015). Multiple hypotheses image segmentation and classification with application to dietary assessment. Biomedical and Health Informatics, IEEE Journal of, 19(1), 377-388