A computer vision method to locate cold spots in foods in microwave sterilization processes

  • Authors:

  • Ram Bhuwan Pandit;Juming Tang;Frank Liu;Galina Mikhaylenko

  • Affiliations:

  • Department of Biological Systems Engineering, Washington State University, 213 L J Smith Hall, Pullman, WA 99164-6120, USA;Department of Biological Systems Engineering, Washington State University, 213 L J Smith Hall, Pullman, WA 99164-6120, USA;Department of Biological Systems Engineering, Washington State University, 213 L J Smith Hall, Pullman, WA 99164-6120, USA;Department of Biological Systems Engineering, Washington State University, 213 L J Smith Hall, Pullman, WA 99164-6120, USA

  • Venue:
  • Pattern Recognition
  • Year:
  • 2007

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Abstract

A major challenge in developing advanced thermal processess based on electromagnetic heating is to determine the location of cold spots in foods. A rapid and reliable method was developed in this study with the aim to effectively locate the cold spot in model food sterilized in microwave systems. The developed method involved application of chemical marker M-2 yield to a model food, mashed potatoes, using computer vision system and an image processing software IMAQ Vision Builder to capture and analyze color patterns after thermal processes. A systematic study was conducted to establish relationships among M-2 yields, color values from captured images of cut food samples, and thermal lethality (F0). Several factors including consistency of imaging background and positions of lights over the diffuser box were considered to standardize the method. To facilitate the comparative study of heating characteristic for different combinations of power levels and F0, a mapping scale using unheated and saturated mashed potato samples was developed by fixing the lowest and upper most gray-scale values. Color values equivalent to gray-level values were positively correlated to F0 and M-2 yield. The specified cold spot location determined by computer vision method was validated in a 915MHz single-mode microwave sterilization system. The results showed that the computer vision method can potentially be used as an effective tool in microwave sterilization process development for regulatory acceptance and industrial applications.