Pill-ID: Matching and retrieval of drug pill images
DC Field | Value | Language |
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dc.contributor.author | Lee, Young-Beom | - |
dc.contributor.author | Park, Unsang | - |
dc.contributor.author | Jain, Anil K. | - |
dc.contributor.author | Lee, Seong-Whan | - |
dc.date.accessioned | 2021-09-06T20:08:45Z | - |
dc.date.available | 2021-09-06T20:08:45Z | - |
dc.date.created | 2021-06-18 | - |
dc.date.issued | 2012-05-01 | - |
dc.identifier.issn | 0167-8655 | - |
dc.identifier.uri | https://scholar.korea.ac.kr/handle/2021.sw.korea/108462 | - |
dc.description.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. (C) 2011 Elsevier B.V. All rights reserved. | - |
dc.language | English | - |
dc.language.iso | en | - |
dc.publisher | ELSEVIER | - |
dc.subject | SCALE | - |
dc.title | Pill-ID: Matching and retrieval of drug pill images | - |
dc.type | Article | - |
dc.contributor.affiliatedAuthor | Jain, Anil K. | - |
dc.contributor.affiliatedAuthor | Lee, Seong-Whan | - |
dc.identifier.doi | 10.1016/j.patrec.2011.08.022 | - |
dc.identifier.wosid | 000302973700013 | - |
dc.identifier.bibliographicCitation | PATTERN RECOGNITION LETTERS, v.33, no.7, pp.904 - 910 | - |
dc.relation.isPartOf | PATTERN RECOGNITION LETTERS | - |
dc.citation.title | PATTERN RECOGNITION LETTERS | - |
dc.citation.volume | 33 | - |
dc.citation.number | 7 | - |
dc.citation.startPage | 904 | - |
dc.citation.endPage | 910 | - |
dc.type.rims | ART | - |
dc.type.docType | Article | - |
dc.description.journalClass | 1 | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
dc.relation.journalResearchArea | Computer Science | - |
dc.relation.journalWebOfScienceCategory | Computer Science, Artificial Intelligence | - |
dc.subject.keywordPlus | SCALE | - |
dc.subject.keywordAuthor | Image retrieval | - |
dc.subject.keywordAuthor | Pill images | - |
dc.subject.keywordAuthor | Illicit drugs | - |
dc.subject.keywordAuthor | Imprints | - |
dc.subject.keywordAuthor | Moment invariants | - |
dc.subject.keywordAuthor | Color histogram | - |
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