吉林大学学报(工学版) ›› 2009, Vol. 39 ›› Issue (增刊2): 344-0348.

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Rapid method for enumeration of Escherichia coli in food based on computer vision

YIN Yong-guang,DING Yun   

  1. College of Biological and Agricultural Engineering, Jilin University, Changchun 130022, China
  • Received:2008-08-07 Online:2009-09-30 Published:2009-09-30

Abstract:

The speciality that the Escherichia coli can ferment lactose to produce acid which can produce depositions and make the indicator's color changed was utilized, an automatic detection system for enumeration of Escherichia coli in food based on color feature recognition technology was designed and the color change degree after incubating for 16 h was used to judge the Escherichia coli counts in the detection samples. The system can automatically extract the H、I、S color vector to act as the input vector and transfer the trained BP neural network to get the Escherichia coli counts. The experiments indicate that comparisons of counts of Escherichia coli by the rapid automatic detection system and by the traditional method closed correlated. Moreover, by using this rapid detection system, the Escherichia coli in food accurately enumerate within 18 h, which is much shorter than the 6 days detection time by the traditional method, which will greatly improve the products sale quality.

Key words: food machinery, machine vision, escherichia coli rapid detection, artificial neural network, color feature recognition

CLC Number: 

  • TS207.4
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