Mobile image based color correction using deblurring

Yu Wang; Chang Xu; Carol Boushey; Fengqing Zhu; Edward J. Delp

doi:10.1117/12.2083133

12 March 2015 Mobile image based color correction using deblurring

Yu Wang, Chang Xu, Carol Boushey, Fengqing Zhu, Edward J. Delp

Proceedings Volume 9401, Computational Imaging XIII; 940107 (2015) https://doi.org/10.1117/12.2083133
Event: SPIE/IS&T Electronic Imaging, 2015, San Francisco, California, United States

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.

Citation Download Citation

Yu Wang, Chang Xu, Carol Boushey, Fengqing Zhu, and Edward J. Delp "Mobile image based color correction using deblurring", Proc. SPIE 9401, Computational Imaging XIII, 940107 (12 March 2015); https://doi.org/10.1117/12.2083133

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