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Authors: David E. Madsen 1 ; Katie S. Payne 1 ; Jason Hagerty 1 ; Nathan Szanto 2 ; Mark Wronkiewicz 3 ; Randy H. Moss 2 and William V. Stoecker 3

Affiliations: 1 Missouri University of Science And Technology and Stoecker & Associates, United States ; 2 Missouri University of Science And Technology, United States ; 3 Stoecker & Associates, United States

ISBN: 978-989-8565-47-1

ISSN: 2184-4321

Keyword(s): Color Space, Color Clustering, Segmentation, Image Analysis, Optical Character Recognition.

Related Ontology Subjects/Areas/Topics: Applications and Services ; Color and Texture Analyses ; Computer Vision, Visualization and Computer Graphics ; Features Extraction ; Image and Video Analysis ; Image Registration ; Medical Image Applications ; Segmentation and Grouping ; Shape Representation and Matching

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.

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Paper citation in several formats:
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, ISSN 2184-4321, pages 378-384. DOI: 10.5220/0004303603780384

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)},


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

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