Dietary Assessment on a Mobile Phone Using Image Processing and Pattern Recognition Techniques: Algorithm Design and System Prototyping

Dietary assessment, while traditionally based on pen-and-paper, is rapidly moving towards automatic approaches. This study describes an Australian automatic food record method and its prototype for dietary assessment via the use of a mobile phone and techniques of image processing and pattern recogn...

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Autores principales: Probst, Yasmine, Nguyen, Duc Thanh, Tran, Minh Khoi, Li, Wanqing
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2015
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4555113/
https://www.ncbi.nlm.nih.gov/pubmed/26225994
http://dx.doi.org/10.3390/nu7085274
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author Probst, Yasmine
Nguyen, Duc Thanh
Tran, Minh Khoi
Li, Wanqing
author_facet Probst, Yasmine
Nguyen, Duc Thanh
Tran, Minh Khoi
Li, Wanqing
author_sort Probst, Yasmine
collection PubMed
description Dietary assessment, while traditionally based on pen-and-paper, is rapidly moving towards automatic approaches. This study describes an Australian automatic food record method and its prototype for dietary assessment via the use of a mobile phone and techniques of image processing and pattern recognition. Common visual features including scale invariant feature transformation (SIFT), local binary patterns (LBP), and colour are used for describing food images. The popular bag-of-words (BoW) model is employed for recognizing the images taken by a mobile phone for dietary assessment. Technical details are provided together with discussions on the issues and future work.
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spelling pubmed-45551132015-09-01 Dietary Assessment on a Mobile Phone Using Image Processing and Pattern Recognition Techniques: Algorithm Design and System Prototyping Probst, Yasmine Nguyen, Duc Thanh Tran, Minh Khoi Li, Wanqing Nutrients Article Dietary assessment, while traditionally based on pen-and-paper, is rapidly moving towards automatic approaches. This study describes an Australian automatic food record method and its prototype for dietary assessment via the use of a mobile phone and techniques of image processing and pattern recognition. Common visual features including scale invariant feature transformation (SIFT), local binary patterns (LBP), and colour are used for describing food images. The popular bag-of-words (BoW) model is employed for recognizing the images taken by a mobile phone for dietary assessment. Technical details are provided together with discussions on the issues and future work. MDPI 2015-07-27 /pmc/articles/PMC4555113/ /pubmed/26225994 http://dx.doi.org/10.3390/nu7085274 Text en © 2015 by the authors; licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Probst, Yasmine
Nguyen, Duc Thanh
Tran, Minh Khoi
Li, Wanqing
Dietary Assessment on a Mobile Phone Using Image Processing and Pattern Recognition Techniques: Algorithm Design and System Prototyping
title Dietary Assessment on a Mobile Phone Using Image Processing and Pattern Recognition Techniques: Algorithm Design and System Prototyping
title_full Dietary Assessment on a Mobile Phone Using Image Processing and Pattern Recognition Techniques: Algorithm Design and System Prototyping
title_fullStr Dietary Assessment on a Mobile Phone Using Image Processing and Pattern Recognition Techniques: Algorithm Design and System Prototyping
title_full_unstemmed Dietary Assessment on a Mobile Phone Using Image Processing and Pattern Recognition Techniques: Algorithm Design and System Prototyping
title_short Dietary Assessment on a Mobile Phone Using Image Processing and Pattern Recognition Techniques: Algorithm Design and System Prototyping
title_sort dietary assessment on a mobile phone using image processing and pattern recognition techniques: algorithm design and system prototyping
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4555113/
https://www.ncbi.nlm.nih.gov/pubmed/26225994
http://dx.doi.org/10.3390/nu7085274
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