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    Image segmentation for image-based dietary assessment: A comparative study

    Access Status
    Fulltext not available
    Authors
    He, Y.
    Khanna, N.
    Boushey, Carol
    Delp, E.
    Date
    2013
    Type
    Conference Paper
    
    Metadata
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    Citation
    He, Y. and Khanna, N. and Boushey, C. and Delp, E. 2013. Image segmentation for image-based dietary assessment: A comparative study, in Proceedings of the International Symposium on Signals, Circuits and Systems (ISSCS), Jul 11-12 2013. Iasi, Romania: IEEE.
    Source Title
    ISSCS 2013 - International Symposium on Signals, Circuits and Systems
    DOI
    10.1109/ISSCS.2013.6651268
    ISBN
    9781467361415
    School
    School of Public Health
    URI
    http://hdl.handle.net/20.500.11937/49949
    Collection
    • Curtin Research Publications
    Abstract

    There is a health crisis in the US related to diet that is further exacerbated by our aging population and sedentary lifestyles. Six of the ten leading causes of death in the United States can be directly linked to diet. Dietary assessment, the process of determining what someone eats during the course of a day, is essential for understanding the link between diet and health. We are developing imaging based tools to automatically obtain accurate estimates of what foods a user consumes. Accurate food segmentation is essential for identifying food items and estimating food portion sizes. In this paper, we present a quantitative evaluation of automatic image segmentation methods for food image analysis used for dietary assessment. The experiments indicate that local variation is more suitable for food image segmentation in general dietary assessment studies where the food images acquired have complex background.

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