• DocumentCode
    116050
  • Title

    Linear regression for pattern recognition

  • Author

    Stephen, Priya ; Jaganathan, Suresh

  • Author_Institution
    Dept. of Comput. Sci. & Eng, Sri Sivasubramaniya Nadar Coll. of Eng., Chennai, India
  • fYear
    2014
  • fDate
    6-8 March 2014
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    This paper presents a novel method for pattern recognition problem in terms of linear regression. Normally, patterns from a single-object class lie on a linear subspace. Using this concept, we develop a linear model representing a probe image as a linear combination of class-specific galleries. Linear Regression Classification (LRC) algorithm for pattern recognition belongs to the category of nearest subspace classification. This algorithm is extensively evaluated on several standard digit and English character databases and our own Tamil character database. A comparative study with different databases and methods clearly reflects the efficiency of LRC approach for pattern recognition.
  • Keywords
    handwritten character recognition; pattern classification; regression analysis; English character databases; LRC approach; Tamil character database; class-specific galleries; linear regression classification algorithm; linear subspace; pattern recognition; probe image; single-object class; standard digit databases; Databases; Linear regression; Mathematical model; Pattern recognition; Testing; Training; Vectors;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Green Computing Communication and Electrical Engineering (ICGCCEE), 2014 International Conference on
  • Conference_Location
    Coimbatore
  • Type

    conf

  • DOI
    10.1109/ICGCCEE.2014.6921393
  • Filename
    6921393