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Related Experiment Video

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Mobile Image Based Color Correction Using Deblurring.

Yu Wang1, Chang Xu1, Carol Boushey2,3

  • 1School of Electrical and Computer Engineering, Purdue University, West Lafayette, Indiana, 47906, USA.

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|June 3, 2017
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Summary
This summary is machine-generated.

This study introduces an enhanced Technology Assisted Dietary Assessment (TADA) System for accurate food tracking. The system improves image quality for better dietary analysis and chronic disease prevention.

Keywords:
color correctionimage deblurring

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Area of Science:

  • Computer Vision
  • Image Processing
  • Nutritional Science

Background:

  • Dietary intake assessment is crucial for chronic disease prevention (e.g., obesity, cancer).
  • Existing methods for dietary assessment can be labor-intensive and prone to inaccuracies.
  • Mobile-based systems offer a promising avenue for automated dietary monitoring.

Purpose of the Study:

  • To enhance the Technology Assisted Dietary Assessment (TADA) System for automatic food and beverage identification and quantification.
  • To improve the accuracy of food image analysis by addressing image quality issues.
  • To develop a robust system for dietary intake monitoring using mobile devices.

Main Methods:

  • Utilized a mobile device to acquire food images.
  • Employed a color checkerboard (fiducial marker) for imaging system calibration.
  • Developed an image quality enhancement technique combining de-blurring and color correction.
  • Implemented an automatic camera shake removal method using saliency maps.
  • Improved polynomial color correction using the LMS color space.

Main Results:

  • Successfully calibrated the imaging system to account for varying lighting conditions.
  • Demonstrated an effective image de-blurring technique for camera shake removal.
  • Achieved improved color correction for more accurate food appearance representation.
  • Enhanced the TADA system's capability for precise food identification and volume estimation.

Conclusions:

  • The proposed image quality enhancement technique significantly improves the performance of the TADA system.
  • Accurate dietary intake assessment via mobile imaging can support public health initiatives.
  • Further development of automated dietary assessment tools holds potential for widespread application in nutrition and health.