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.
| Original language | English |
|---|---|
| Pages (from-to) | 904-910 |
| Number of pages | 7 |
| Journal | Pattern Recognition Letters |
| Volume | 33 |
| Issue number | 7 |
| DOIs | |
| Publication status | Published - 2012 May 1 |
Bibliographical note
Funding Information:The authors thank Dr. Mark Tahtouh of the Australian Federal Police for providing drug pill images. Anil K. Jain’s research was partially supported by WCU (World Class University) program through the National Research Foundation of Korea funded by the Ministry of Education, Science and Technology ( R31-10008 ) to Korea university.
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 16 Peace, Justice and Strong Institutions
Keywords
- Color histogram
- Illicit drugs
- Image retrieval
- Imprints
- Moment invariants
- Pill images
ASJC Scopus subject areas
- Software
- Signal Processing
- Computer Vision and Pattern Recognition
- Artificial Intelligence
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