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Proceedings Paper

Mobile image based color correction using deblurring
Author(s): Yu Wang; Chang Xu; Carol Boushey; Fengqing Zhu; Edward J. Delp
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Paper Abstract

Dietary intake, the process of determining what someone eats during the course of a day, provides valuable insights for mounting intervention programs for prevention of many chronic diseases such as obesity and cancer. The goals of the Technology Assisted Dietary Assessment (TADA) System, developed at Purdue University, is to automatically identify and quantify foods and beverages consumed by utilizing food images acquired with a mobile device. Color correction serves as a critical step to ensure accurate food identification and volume estimation. We make use of a specifically designed color checkerboard (i.e. a fiducial marker) to calibrate the imaging system so that the variations of food appearance under different lighting conditions can be determined. In this paper, we propose an image quality enhancement technique by combining image de-blurring and color correction. The contribution consists of introducing an automatic camera shake removal method using a saliency map and improving the polynomial color correction model using the LMS color space.

Paper Details

Date Published: 12 March 2015
PDF: 12 pages
Proc. SPIE 9401, Computational Imaging XIII, 940107 (12 March 2015); doi: 10.1117/12.2083133
Show Author Affiliations
Yu Wang, Purdue Univ. (United States)
Chang Xu, Purdue Univ. (United States)
Carol Boushey, Purdue Univ. (United States)
Univ. of Hawai'i Cancer Ctr. (United States)
Fengqing Zhu, Purdue Univ. (United States)
Edward J. Delp, Purdue Univ. (United States)

Published in SPIE Proceedings Vol. 9401:
Computational Imaging XIII
Charles A. Bouman; Ken D. Sauer, Editor(s)

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