An Image Analysis Environment for Species Identification of Food Contaminating Beetles

Authors

  • Daniel Martin Arizona State University
  • Hongjian Ding US Food and Drug Adminstration
  • Leihong Wu US Food and Drug Administration
  • Howard Semey US Food and Drug Adminstration
  • Amy Barnes US Food and Drug Adminstration
  • Darryl Langley US Food and Drug Adminstration
  • Su Inn Park Samsung Austin Semiconductor LLC
  • Zhichao Liu US Food and Drug Administration
  • Weida Tong US Food and Drug Administration
  • Joshua Xu US Food and Drug Administration

DOI:

https://doi.org/10.1609/aaai.v30i1.9846

Keywords:

Food Safety Inspection, Food Contamination, Image Analysis, Machine Learning

Abstract

Food safety is vital to the well-being of society; therefore, it is important to inspect food products to ensure minimal health risks are present. The presence of certain species of insects, especially storage beetles, is a reliable indicator of possible contamination during storage and food processing. However, the current approach of identifying species by visual examination of insect fragments is rather subjective and time-consuming. To aid this inspection process, we have developed in collaboration with FDA food analysts some image analysis-based machine intelligence to achieve species identification with up to 90% accuracy. The current project is a continuation of this development effort. Here we present an image analysis environment that allows practical deployment of the machine intelligence on computers with limited processing power and memory. Using this environment, users can prepare input sets by selecting images for analysis, and inspect these images through the integrated panning and zooming capabilities. After species analysis, the results panel allows the user to compare the analyzed images with reference images of the proposed species. Further additions to this environment should include a log of previously analyzed images, and eventually extend to interaction with a central cloud repository of images through a web-based interface.

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Published

2016-03-05

How to Cite

Martin, D., Ding, H., Wu, L., Semey, H., Barnes, A., Langley, D., Park, S. I., Liu, Z., Tong, W., & Xu, J. (2016). An Image Analysis Environment for Species Identification of Food Contaminating Beetles. Proceedings of the AAAI Conference on Artificial Intelligence, 30(1). https://doi.org/10.1609/aaai.v30i1.9846