Pill-ID: Matching and retrieval of drug pill images

Young Beom Lee, Unsang Park, Anil K. Jain, Seong Whan Lee

Research output: Contribution to journalArticle

24 Citations (Scopus)

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 languageEnglish
Pages (from-to)904-910
Number of pages7
JournalPattern Recognition Letters
Volume33
Issue number7
DOIs
Publication statusPublished - 2012 May 1

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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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