DETECTION OF LOTUS ROOT CONTAMINANTS USING INTELLIGENT VISUAL MACHINE VISION TECHNIQUES
| Autor: | Yuan Hao, Samuel Britwum Wilson, Jianrong Cia, Xukang Bao, Emmanuel Asamoah |
|---|---|
| Rok vydání: | 2021 |
| Předmět: |
biology
Lotus root Machine vision Computer science business.industry InformationSystems_INFORMATIONSYSTEMSAPPLICATIONS Lotus ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION Process (computing) ComputingMilieux_LEGALASPECTSOFCOMPUTING Image processing Image segmentation biology.organism_classification Edge detection Machine vision system Computer vision Artificial intelligence business |
| Zdroj: | Journal of Food Industry. 5:1 |
| ISSN: | 1948-545X |
| DOI: | 10.5296/jfi.v5i1.17813 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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