Automatic Pill Identification from Pillbox Images

David E. Madsen, Katie S. Payne, Jason Hagerty, Nathan Szanto, Mark Wronkiewicz, Randy H. Moss, William V. Stoecker

2013

Abstract

There is a vital need for fast and accurate recognition of medicinal tablets and capsules. Efforts to date have centered on automatic segmentation, color and shape identification. Our system combines these with pre-processing before imprint recognition. Using the National Library of Medicine Pillbox database, regression analysis applied to automatic color and shape recognition allows for successful pill identification. Measured errors for the subtasks of segmentation and color recognition for this database are 1.9% and 2.2%, respectively. Imprint recognition with optical character recognition (OCR) is key to exact pill ID, but remains a challenging problem, therefore overall recognition accuracy is not yet known.

Paper Citation

in Harvard Style

E. Madsen D., S. Payne K., Hagerty J., Szanto N., Wronkiewicz M., H. Moss R. and V. Stoecker W. (2013). Automatic Pill Identification from Pillbox Images . In Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2013) ISBN 978-989-8565-47-1, pages 378-384. DOI: 10.5220/0004303603780384

in Bibtex Style

@conference{visapp13,
author={David E. Madsen and Katie S. Payne and Jason Hagerty and Nathan Szanto and Mark Wronkiewicz and Randy H. Moss and William V. Stoecker},
title={Automatic Pill Identification from Pillbox Images},
booktitle={Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2013)},
year={2013},
pages={378-384},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004303603780384},
isbn={978-989-8565-47-1},
}

in EndNote Style

TY - CONF
JO - Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2013)
TI - Automatic Pill Identification from Pillbox Images
SN - 978-989-8565-47-1
AU - E. Madsen D.
AU - S. Payne K.
AU - Hagerty J.
AU - Szanto N.
AU - Wronkiewicz M.
AU - H. Moss R.
AU - V. Stoecker W.
PY - 2013
SP - 378
EP - 384
DO - 10.5220/0004303603780384