Image-based Ear Biometric Smartphone App for Patient Identification in Field Settings

Sarah Adel Bargal, Alexander Welles, Cliff R. Chan, Samuel Howes, Stan Sclaroff, Elizabeth Ragan, Courtney Johnson, Christopher Gill

2015

Abstract

We present a work in progress of a computer vision application that would directly impact the delivery of healthcare in underdeveloped countries. We describe the development of an image-based smartphone application prototype for ear biometrics. The application targets the public health problem of managing medical records at on-site medical clinics in less developed countries where many individuals do not hold IDs. The domain presents challenges for an ear biometric system, including varying scale, rotation, and illumination. It was not clear which feature descriptors would work best for the application, so a comparative study of three ear biometric extraction techniques was performed, one of which was used to develop an iOS application prototype to establish the identity of an individual using a smartphone camera image. A pilot study was then conducted on the developed application to test feasibility in naturalistic settings.

Paper Citation

in Harvard Style

Adel Bargal S., Welles A., R. Chan C., Howes S., Sclaroff S., Ragan E., Johnson C. and Gill C. (2015). Image-based Ear Biometric Smartphone App for Patient Identification in Field Settings . In Proceedings of the 10th International Conference on Computer Vision Theory and Applications - Volume 3: VISAPP, (VISIGRAPP 2015) ISBN 978-989-758-091-8, pages 171-179. DOI: 10.5220/0005342201710179

in Bibtex Style

@conference{visapp15,
author={Sarah Adel Bargal and Alexander Welles and Cliff R. Chan and Samuel Howes and Stan Sclaroff and Elizabeth Ragan and Courtney Johnson and Christopher Gill},
title={Image-based Ear Biometric Smartphone App for Patient Identification in Field Settings},
booktitle={Proceedings of the 10th International Conference on Computer Vision Theory and Applications - Volume 3: VISAPP, (VISIGRAPP 2015)},
year={2015},
pages={171-179},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005342201710179},
isbn={978-989-758-091-8},
}

in EndNote Style

TY - CONF
JO - Proceedings of the 10th International Conference on Computer Vision Theory and Applications - Volume 3: VISAPP, (VISIGRAPP 2015)
TI - Image-based Ear Biometric Smartphone App for Patient Identification in Field Settings
SN - 978-989-758-091-8
AU - Adel Bargal S.
AU - Welles A.
AU - R. Chan C.
AU - Howes S.
AU - Sclaroff S.
AU - Ragan E.
AU - Johnson C.
AU - Gill C.
PY - 2015
SP - 171
EP - 179
DO - 10.5220/0005342201710179