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dc.contributor.authorHe, Y.
dc.contributor.authorKhanna, N.
dc.contributor.authorBoushey, Carol
dc.contributor.authorDelp, E.
dc.date.accessioned2017-03-15T22:16:51Z
dc.date.available2017-03-15T22:16:51Z
dc.date.created2017-02-26T19:31:37Z
dc.date.issued2013
dc.identifier.citationHe, 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.
dc.identifier.urihttp://hdl.handle.net/20.500.11937/49949
dc.identifier.doi10.1109/ISSCS.2013.6651268
dc.description.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.

dc.titleImage segmentation for image-based dietary assessment: A comparative study
dc.typeConference Paper
dcterms.source.titleISSCS 2013 - International Symposium on Signals, Circuits and Systems
dcterms.source.seriesISSCS 2013 - International Symposium on Signals, Circuits and Systems
dcterms.source.isbn9781467361415
curtin.departmentSchool of Public Health
curtin.accessStatusFulltext not available


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