Mobile image based color correction using deblurring

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...

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Main Authors: Wang, Y., Xu, C., Boushey, Carol, Zhu, F., Delp, E.
Format: Conference Paper
Published: SPIE 2015
Online Access:http://hdl.handle.net/20.500.11937/51011
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author Wang, Y.
Xu, C.
Boushey, Carol
Zhu, F.
Delp, E.
author_facet Wang, Y.
Xu, C.
Boushey, Carol
Zhu, F.
Delp, E.
author_sort Wang, Y.
building Curtin Institutional Repository
collection Online Access
description 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.
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institution Curtin University Malaysia
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spelling curtin-20.500.11937-510112018-03-29T09:09:26Z Mobile image based color correction using deblurring Wang, Y. Xu, C. Boushey, Carol Zhu, F. Delp, E. 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. 2015 Conference Paper http://hdl.handle.net/20.500.11937/51011 10.1117/12.2083133 SPIE restricted
spellingShingle Wang, Y.
Xu, C.
Boushey, Carol
Zhu, F.
Delp, E.
Mobile image based color correction using deblurring
title Mobile image based color correction using deblurring
title_full Mobile image based color correction using deblurring
title_fullStr Mobile image based color correction using deblurring
title_full_unstemmed Mobile image based color correction using deblurring
title_short Mobile image based color correction using deblurring
title_sort mobile image based color correction using deblurring
url http://hdl.handle.net/20.500.11937/51011