• DocumentCode
    1361090
  • Title

    Image Retrieval in Forensics: Tattoo Image Database Application

  • Author

    Lee, Jung-Eun ; Jin, Rong ; Jain, Anil K. ; Tong, Wei

  • Author_Institution
    Michigan State Univ., East Lansing, MI, USA
  • Volume
    19
  • Issue
    1
  • fYear
    2012
  • Firstpage
    40
  • Lastpage
    49
  • Abstract
    In this article, we took an unsupervised approach in designing appropriate similarity measures to explicitly address the challenge arising from low-quality tattoo image matching. In the future, we plan to improve the matching algorithm by exploring both super- vised and semisupervised learning algorithms. Besides tattoos, other types of soft forensic evidence can be collected and managed in the form of images, such as shoe prints and gang graffiti images. Although Tattoo-ID focuses on tattoo image matching and retrieval, the underlying techniques developed in the Tattoo-ID system can be adopted to other forensic image databases.15 Other types of soft forensic image evidence might include shoeprints and gang graffiti images. In the future, we plan to extend the Tattoo-ID system to different application domains.
  • Keywords
    forensic science; image matching; image retrieval; law administration; learning (artificial intelligence); forensics; gang graffiti images; image retrieval; semisupervised learning algorithm; shoe prints; similarity measures; soft forensic evidence; supervised learning algorithm; tattoo image database application; tattoo image matching; tattoo image retrieval; unsupervised approach; Content management; Digital forensics; Fingerprint recognition; Forensics; Image retrieval; Iris recognition; Tattoo-ID system; biometrics; forensic databases; multimedia; near-duplicate image retrieval; tattoo images;
  • fLanguage
    English
  • Journal_Title
    MultiMedia, IEEE
  • Publisher
    ieee
  • ISSN
    1070-986X
  • Type

    jour

  • DOI
    10.1109/MMUL.2011.59
  • Filename
    6060794