Image enhancement and quality measures for dietary assessment using mobile devices

Chang Xu; Fengqing Zhu; Nitin Khanna; Carol J. Boushey; Edward J. Delp

doi:10.1117/12.909949

10 February 2012 Image enhancement and quality measures for dietary assessment using mobile devices

Chang Xu, Fengqing Zhu, Nitin Khanna, Carol J. Boushey, Edward J. Delp

Proceedings Volume 8296, Computational Imaging X; 82960Q (2012) https://doi.org/10.1117/12.909949
Event: IS&T/SPIE Electronic Imaging, 2012, Burlingame, California, United States

Abstract

Measuring accurate dietary intake is considered to be an open research problem in the nutrition and health fields. We are developing a system, known as the mobile device food record (mdFR), to automatically identify and quantify foods and beverages consumed based on analyzing meal images captured with a mobile device. The mdFR makes use of a fiducial marker and other contextual information to calibrate the imaging system so that accurate amounts of food can be estimated from the scene. Food identification is a difficult problem since foods can dramatically vary in appearance. Such variations may arise not only from non-rigid deformations and intra-class variability in shape, texture, color and other visual properties, but also from changes in illumination and viewpoint. To address the color consistency problem, this paper describes illumination quality assessment methods implemented on a mobile device and three post color correction methods.

Citation Download Citation

Chang Xu, Fengqing Zhu, Nitin Khanna, Carol J. Boushey, and Edward J. Delp "Image enhancement and quality measures for dietary assessment using mobile devices", Proc. SPIE 8296, Computational Imaging X, 82960Q (10 February 2012); https://doi.org/10.1117/12.909949

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