Pill-ID: Matching and retrieval of drug pill images

Authors:
Young-Beom Lee;Unsang Park;Anil K. Jain;Seong-Whan Lee
Affiliations:
Department of Brain and Cognitive Engineering, Korea University, Anam-dong, Seongbuk-gu, Seoul 136-713, South Korea;Department of Computer Science and Engineering, Michigan State University, E. Lansing, MI 48824, USA;Department of Brain and Cognitive Engineering, Korea University, Anam-dong, Seongbuk-gu, Seoul 136-713, South Korea and Department of Computer Science and Engineering, Michigan State University, E ...;Department of Brain and Cognitive Engineering, Korea University, Anam-dong, Seongbuk-gu, Seoul 136-713, South Korea
Venue:
Pattern Recognition Letters
Year:
2012

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Abstract

Worldwide, law enforcement agencies are encountering a substantial increase in the number of illicit drug pills being circulated in our society. Identifying the source and manufacturer of these illicit drugs will help deter drug-related crimes. We have developed an automatic system, called Pill-ID to match drug pill images based on several features (i.e., imprint, color, and shape) of the tablet. The color and shape information is encoded as a three-dimensional histogram and invariant moments, respectively. The imprint on the pill is encoded as feature vectors derived from SIFT and MLBP descriptors. Experimental results using a database of drug pill images (1029 illicit drug pill images and 14,002 legal drug pill images) show 73.04% (84.47%) rank-1 (rank-20) retrieval accuracy.