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Low Complexity Image Quality Measures for Dietary Assessment Using Mobile Devices.

Chang Xu1, Nitin Khanna1, Carol J Boushey2

  • 1School of Electrical and Computer Engineering Purdue University, West Lafayette, Indiana, USA.

ISM ... : ... IEEE International Symposium on Multimedia ... : Proceedings. IEEE International Symposium on Multimedia
|June 3, 2017
PubMed
Summary

Accurately measuring diet is key for managing chronic diseases. This study introduces simple image analysis tools for mobile devices to assess food intake from meal photos, aiding in dietary assessment.

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Area of Science:

  • Nutrition Science
  • Computer Vision
  • Biomedical Engineering

Background:

  • Diet plays a crucial role in the development and management of chronic diseases like heart disease, diabetes, and obesity.
  • Accurate dietary assessment is essential for public health and personalized medicine.
  • Existing dietary assessment methods can be time-consuming and prone to recall bias.

Purpose of the Study:

  • To develop and evaluate low-complexity image quality measures for food image analysis.
  • To enable accurate food identification and quantity estimation from single meal images on mobile devices.
  • To provide immediate feedback to users on image quality for improved dietary data collection.

Main Methods:

  • Development of image analysis algorithms for food recognition and portion size estimation.

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  • Implementation of low-complexity image quality assessment metrics suitable for mobile platforms.
  • Integration of these measures into a user-facing application providing real-time feedback.

    • Main Results:

    • Demonstrated the feasibility of using single meal images for food identification and quantification.
    • Validated the effectiveness of low-complexity image quality measures on handheld devices.
    • Showcased the potential for immediate user feedback to enhance image acquisition for dietary analysis.

    Conclusions:

    • Low-complexity image quality measures are effective for mobile-based dietary assessment tools.
    • Image analysis of meals holds promise for improving the accuracy and accessibility of dietary intake monitoring.
    • This technology can support chronic disease management through better dietary tracking.