• DocumentCode
    1632501
  • Title

    Home security system based on Fuzzy k-NN Classifier

  • Author

    Junoh, A.K. ; Mansor, Muhammad Naufal

  • Author_Institution
    Ind. Math. Res. Group (IMRG), Univ. Malaysia Perlis, Kangar, Malaysia
  • Volume
    2
  • fYear
    2012
  • Firstpage
    361
  • Lastpage
    363
  • Abstract
    A Fuzzy k-nn Classifier for home security system we describe in this paper. Images were taken in uncontrolled indoor environment using video cameras of various qualities. Database contains 4,005 static images (in visible and infrared spectrum) of 267 subjects. Images from different quality cameras should mimic real-world conditions and enable robust face recognition algorithms testing, emphasizing different law enforcement and surveillance use case scenarios. In addition to database description, this paper also elaborates on possible uses of the database and proposes a testing protocol. A baseline Principal Component Analysis (PCA) face recognition algorithm was tested following the proposed protocol based on k-nn Classifier. Other researchers can use these test results as a control algorithm performance score when testing their own algorithms on this dataset. Database is available to research community through the procedure described at http://www.lrv.fri.uni-lj.si/facedb.html.
  • Keywords
    face recognition; home computing; pattern classification; security; video surveillance; face recognition algorithms; fuzzy k-NN classifier; home security system; infrared spectra; principal component analysis; static image; testing protocol; uncontrolled indoor environment; video camera; visible spectra; Accuracy; Algorithm design and analysis; Classification algorithms; Face; Face detection; Face recognition; Principal component analysis; Fuzzy k-NN; Image Processing; PCA; Surveillance System;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Instrumentation & Measurement, Sensor Network and Automation (IMSNA), 2012 International Symposium on
  • Conference_Location
    Sanya
  • Print_ISBN
    978-1-4673-2465-6
  • Type

    conf

  • DOI
    10.1109/MSNA.2012.6324594
  • Filename
    6324594