Edible Bird Nest Processing using Machine Vision and Robotic Arm

Authors

  • Yuvarajoo Subramaniam Malaysia Japan Institute of Technolgy (MJIIT), Universiti Teknologi Malaysia, 81310 UTM Johor Bahru, Johor, Malaysia
  • Yeong Che Fai Centre for Artificial Intelligence and Robotics, Faculty of Electrical Engineering, Universiti Teknologi Malaysia, 81310 Johor Bahru, Johor, Malaysia
  • Eileen Su Lee Ming Faculty of Electrical Engineering, Universiti Teknologi Malaysia, 81310 UTM Johor Bahru, Johor, Malaysia

DOI:

https://doi.org/10.11113/jt.v72.3889

Keywords:

Edible, bird nest, automation, vision, robotic

Abstract

Edible Bird nest food product is one of the demanding food product in food production industry. Government looking into ways to improve this industry to boost the economy. Many large scale production are being operated around Malaysia. One of the major difficulties faced in processing the bird nest is to remove its impurities or more formerly known as dirt. Current conventional cleaning method which is manual cleaning is not cost effective and time consuming. Furthermore, it also requires large number of workforce to be used for processing small quantities of bird nest. This paper presents an automated system which utilizes machine vision system and an industrial robot to accomplish a better processing system for edible bird nest. This system offers great advantage compared to conventional process by reducing the time consumed for processing and increase the efficiency.

References

Hobbs, J. J. 2004. Problems in the Harvest of Edible Birds’ Nests in Sarawak and Sabah, Malaysian Borneo. Biodivers. Conserv. 13: 2209–2226.

Teo, W. C. 2009. A Study on Suitable Habitat for Swiftlet Farming. 1(1): 1–7.

Wong, R. S. Y. 2013. Edible Bird’s Nest: Food or Medicine. J. Integr. Med. 19(9): 643–649.

Jong, C. H., Tay, K. M. and Lim, C. P. 2013. Application of the Fuzzy Failure Mode and Effect Analysis Methodology to Edible Bird Nest Processing. Comput. Electron. Agric. 96: 90–108.

Marcone, M. F. 2005. Characterization of the Edible Bird’s Nest the ‘Caviar of the East. Food Res. Int. 38: 1125–1134.

Chua, K. H., Lee, T. H., Nagandran, K., Md Yahaya, N. H., Lee, C. T. , Tjih, E. T. T. and Abdul Aziz, R. 2013. Edible Bird’s Nest Extract as a Chondro-protective Agent for Human Chondrocytes Isolated from Osteoarthritic Knee: In Vitro Study. BMC Complement. Altern. Med. 13(1): 19.

Malamas, E. N., Petrakis, E. G., Zervakis, M., Petit, L. and Legat, J. D. 2003. A Survey on Industrial Vision Systems, Applications and Tools. Image Vis. Comput. 21(2): 171–188.

Li, Q., Wang, M. and Gu, W. 2002. Computer Vision Based System for Apple Surface Defect Detection. Comput. Electron. Agric. 36(2.3): 215–223.

Thomas, A. D. H., Rodd, M. G., Holt, J. D. and Neill, C. J. 1995. Real-time Industrial Visual Inspection: A Review. Real-Time Imaging. 1(2): 139–158.

Will, D. J. and Technikon, P. E. 2004. Design and Implementation Of Robotic. Port Elizabeth Technikon.

Downloads

Published

2015-01-05

How to Cite

Edible Bird Nest Processing using Machine Vision and Robotic Arm. (2015). Jurnal Teknologi, 72(2). https://doi.org/10.11113/jt.v72.3889