Esophagus Detection for Halal Classification in SYCUT

Authors

  • Nor Aziah Amirah Nor Muhammad Centre for Artificial Intelligence & Robotics (CAIRO), Universiti Teknologi Malaysia, 54100 Kuala Lumpur, Malaysia. Malaysia-Japan International Institute of Technology, Universiti Teknologi Malaysia, 54100 Kuala Lumpur, Malaysia.
  • Rubiyah Yusof Centre for Artificial Intelligence & Robotics (CAIRO), Universiti Teknologi Malaysia, 54100 Kuala Lumpur, Malaysia. Malaysia-Japan International Institute of Technology, Universiti Teknologi Malaysia, 54100 Kuala Lumpur, Malaysia.
  • Reza Arfa Centre for Artificial Intelligence & Robotics (CAIRO), Universiti Teknologi Malaysia, 54100 Kuala Lumpur, Malaysia. Malaysia-Japan International Institute of Technology, Universiti Teknologi Malaysia, 54100 Kuala Lumpur, Malaysia.
  • Ridzuan Yunus Centre for Artificial Intelligence & Robotics (CAIRO), Universiti Teknologi Malaysia, 54100 Kuala Lumpur, Malaysia.
  • Nordinah Ismail Malaysia-Japan International Institute of Technology, Universiti Teknologi Malaysia, 54100 Kuala Lumpur, Malaysia.

Keywords:

Chicken poultry, esophagus detection, halal, object detection, vision

Abstract

According to the Islamic Law, one of the procedures in halal slaughtering of chicken is the step of severing the trachea, esophagus and both the carotid arteries and jugular veins to accelerate the chicken’s bleeding and death. Syariah Compliance Automated Chicken Processing System (SYCUT) uses the Vision Inspection Technology to detect and classify whether a chicken is halal or not. The lack of quality and halal assurance in chicken processing industry made it a need to produce such technology. The system implements image processing techniques and artificial intelligence approach, particularly the Viola and Jones object detection framework for esophagus detection. The results of the experiment from two different sites (Az-Zain and 3P) are 81.8% and 55% respectively. The detection module of those two sites show results of 95.6% and 93.5% which are the accuracy as good as human personnel.

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Published

05-09-2019

How to Cite

Nor Muhammad, N. A. A., Yusof, R., Arfa, R., Yunus, R., & Ismail, N. (2019). Esophagus Detection for Halal Classification in SYCUT. International Journal of Integrated Engineering, 11(4). https://penerbit.uthm.edu.my/ojs/index.php/ijie/article/view/4196