title: Determination of food portion size by image processing.
abstract: Overweight and obesity have become an epidemic in many parts of the world threatening the health of over one billion people. In order to combat this epidemic effectively, it is desirable to develop new methods to monitor individual's food intake and provide quantitative information about the nutrients and calories consumed in people's daily life. We present an electronic photographic approach and associated image processing algorithms to estimate food portion size, which is then utilized to obtain the required information. Our experiments show that our approach is accurate, providing an effective tool for people to track their nutritional and energy intake.
authors.affiliation: School of Medicine, University of Pittsburgh, Pittsburgh, PA 15260, USA. mrsun@neuronet.pitt.edu
authors.forename: Mingui
authors.initials: M
authors.lastname: Sun
authors.forename: Qiang
authors.initials: Q
authors.lastname: Liu
authors.forename: Karel
authors.initials: K
authors.lastname: Schmidt
authors.forename: Jie
authors.initials: J
authors.lastname: Yang
authors.forename: Ning
authors.initials: N
authors.lastname: Yao
authors.forename: John D
authors.initials: JD
authors.lastname: Fernstrom
authors.forename: Madelyn H
authors.initials: MH
authors.lastname: Fernstrom
authors.forename: James P
authors.initials: JP
authors.lastname: DeLany
authors.forename: Robert J
authors.initials: RJ
authors.lastname: Sclabassi
mesh_terms: D000465:Algorithms; D001185:Artificial Intelligence; D004032:Diet; D004435:Eating / Q000502:physiology*; D005247:Feeding Behavior / Q000502:physiology*; D005504:Food Analysis / Q000379:methods*; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D010363:Pattern Recognition, Automated / Q000379:methods*; D010781:Photography / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity