A Research and Implementation of Image-based Food Recognition System

碩士 === 國立高雄應用科技大學 === 資訊工程系 === 102 === A local orientation descriptor (LOD) for nutrition analysis by quantity estimation is proposed. By observing nutrition properties, a texture-based LOD is designed to extract discriminant information, frequency and length among food items. Prior to classificati...

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Main Authors: Ken-Wei Lin, 林鏗為
Other Authors: Ju-Chin Chen
Format: Others
Language:zh-TW
Published: 2014
Online Access:http://ndltd.ncl.edu.tw/handle/7cgp5k
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spelling ndltd-TW-102KUAS03920082019-07-04T05:57:52Z http://ndltd.ncl.edu.tw/handle/7cgp5k A Research and Implementation of Image-based Food Recognition System 研究與實作一基於影像之食物辨識系統 Ken-Wei Lin 林鏗為 碩士 國立高雄應用科技大學 資訊工程系 102 A local orientation descriptor (LOD) for nutrition analysis by quantity estimation is proposed. By observing nutrition properties, a texture-based LOD is designed to extract discriminant information, frequency and length among food items. Prior to classification, food detection is a challenging problem due to significant variety of backgrounds and containers. Thus, two food region detectors are designed in this study. In addition, nutrition quantity is estimated using coins as reference objects. Three types of features, normalized colour, density, and symmetry properties are extracted for coin classification. Experimental results show that the proposed LOD outperforms existing object recognition features. Ju-Chin Chen 陳洳瑾 2014 學位論文 ; thesis 20 zh-TW
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description 碩士 === 國立高雄應用科技大學 === 資訊工程系 === 102 === A local orientation descriptor (LOD) for nutrition analysis by quantity estimation is proposed. By observing nutrition properties, a texture-based LOD is designed to extract discriminant information, frequency and length among food items. Prior to classification, food detection is a challenging problem due to significant variety of backgrounds and containers. Thus, two food region detectors are designed in this study. In addition, nutrition quantity is estimated using coins as reference objects. Three types of features, normalized colour, density, and symmetry properties are extracted for coin classification. Experimental results show that the proposed LOD outperforms existing object recognition features.
author2 Ju-Chin Chen
author_facet Ju-Chin Chen
Ken-Wei Lin
林鏗為
author Ken-Wei Lin
林鏗為
spellingShingle Ken-Wei Lin
林鏗為
A Research and Implementation of Image-based Food Recognition System
author_sort Ken-Wei Lin
title A Research and Implementation of Image-based Food Recognition System
title_short A Research and Implementation of Image-based Food Recognition System
title_full A Research and Implementation of Image-based Food Recognition System
title_fullStr A Research and Implementation of Image-based Food Recognition System
title_full_unstemmed A Research and Implementation of Image-based Food Recognition System
title_sort research and implementation of image-based food recognition system
publishDate 2014
url http://ndltd.ncl.edu.tw/handle/7cgp5k
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