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Detection Of Lotus Root Contaminants Using Intelligent Visual Machine Vision Techniques

Author

Listed:
  • Yuan Hao
  • Samuel Britwum Wilson
  • Emmanuel Asamoah
  • Jianrong Cia
  • Xukang Bao

Abstract

Lotus root, which is a water plant cherished by people in the Asian continent and some other parts of the world, is manually inspected for quality by experts to detect impurities. There is the need to update this inspection process in order to improve the quality and safety of lotus root. Machine vision systems and techniques are used for consistent, efficient, effective, and reliable inspection of images. The lotus root inspection system has been proposed to inspect the lotus roots for impurities. The detection algorithms use the size, shape, texture and color of the lotus root images as parameters to analyze the quality of lotus roots. The lotus root undergoes some processes before image acquisition and image processing. The camera and illumination used, in collaboration with the edge detection, and image segmentation techniques, efficiently and effectively exposed the impurities in the lotus root at a much faster rate. Also, it is less expensive compared to the traditional human inspections.

Suggested Citation

  • Yuan Hao & Samuel Britwum Wilson & Emmanuel Asamoah & Jianrong Cia & Xukang Bao, 2021. "Detection Of Lotus Root Contaminants Using Intelligent Visual Machine Vision Techniques," Journal of Food Industry, Macrothink Institute, vol. 5(1), pages 117-117, December.
  • Handle: RePEc:mth:jfi888:v:5:y:2021:i:1:p:117
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    JEL classification:

    • R00 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General - - - General
    • Z0 - Other Special Topics - - General

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