@inproceedings{c22fc0bc45f24a70962608498bdb0527,
title = "A new accurate pill recognition system using imprint information",
abstract = "Great achievements in modern medicine benefit human beings. Also, it has brought about an explosive growth of pharmaceuticals that current in the market. In daily life, pharmaceuticals sometimes confuse people when they are found unlabeled. In this paper, we propose an automatic pill recognition technique to solve this problem. It functions mainly based on the imprint feature of the pills, which is extracted by proposed MSWT (modified stroke width transform) and described by WSC (weighted shape context). Experiments show that our proposed pill recognition method can reach an accurate rate up to 92.03% within top 5 ranks when trying to classify more than 10 thousand query pill images into around 2000 categories.",
keywords = "Feature extraction, Image retrieval, Modified Stroke Width Transform (MSWT), Pill recognition, Weighted Shape Context (WSC)",
author = "Zhiyuan Chen and Kamata, {Sei Ichiro}",
year = "2013",
doi = "10.1117/12.2051168",
language = "English",
isbn = "9780819499967",
series = "Proceedings of SPIE - The International Society for Optical Engineering",
publisher = "SPIE",
booktitle = "Sixth International Conference on Machine Vision, ICMV 2013",
note = "6th International Conference on Machine Vision, ICMV 2013 ; Conference date: 16-11-2013 Through 17-11-2013",
}