The development of a line-scan imaging algorithm for the detection of fecal contamination on leafy greens

Chun Chieh Yang, Moon S. Kim, Yung-Kun Chuang, Hoyoung Lee

研究成果: 書貢獻/報告類型會議貢獻

摘要

This paper reports the development of a multispectral algorithm, using the line-scan hyperspectral imaging system, to detect fecal contamination on leafy greens. Fresh bovine feces were applied to the surfaces of washed loose baby spinach leaves. A hyperspectral line-scan imaging system was used to acquire hyperspectral fluorescence images of the contaminated leaves. Hyperspectral image analysis resulted in the selection of the 666 nm and 688 nm wavebands for a multispectral algorithm to rapidly detect feces on leafy greens, by use of the ratio of fluorescence intensities measured at those two wavebands (666 nm over 688 nm). The algorithm successfully distinguished most of the lowly diluted fecal spots (0.05 g feces/ml water and 0.025 g feces/ml water) and some of the highly diluted spots (0.0125 g feces/ml water and 0.00625 g feces/ml water) from the clean spinach leaves. The results showed the potential of the multispectral algorithm with line-scan imaging system for application to automated food processing lines for food safety inspection of leafy green vegetables.
原文英語
主出版物標題Sensing for Agriculture and Food Quality and Safety V
8721
DOIs
出版狀態已發佈 - 2013
對外發佈
事件Sensing for Agriculture and Food Quality and Safety V - Baltimore, MD, 美国
持續時間: 四月 30 2013五月 1 2013

會議

會議Sensing for Agriculture and Food Quality and Safety V
國家/地區美国
城市Baltimore, MD
期間4/30/135/1/13

ASJC Scopus subject areas

  • 應用數學
  • 電腦科學應用
  • 電氣與電子工程
  • 電子、光磁材料
  • 凝聚態物理學

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