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Proceedings Paper

Image enhancement and quality measures for dietary assessment using mobile devices
Author(s): Chang Xu; Fengqing Zhu; Nitin Khanna; Carol J. Boushey; Edward J. Delp
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Paper 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.

Paper Details

Date Published: 10 February 2012
PDF: 10 pages
Proc. SPIE 8296, Computational Imaging X, 82960Q (10 February 2012); doi: 10.1117/12.909949
Show Author Affiliations
Chang Xu, Purdue Univ. (United States)
Fengqing Zhu, Purdue Univ. (United States)
Nitin Khanna, Purdue Univ. (United States)
Carol J. Boushey, Purdue Univ. (United States)
Univ. of Hawaii Cancer Ctr. (United States)
Edward J. Delp, Purdue Univ. (United States)

Published in SPIE Proceedings Vol. 8296:
Computational Imaging X
Charles A. Bouman; Ilya Pollak; Patrick J. Wolfe, Editor(s)

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