• DocumentCode
    3398193
  • Title

    Bangla Hand Written digit recognition using supervised locally linear embedding algorithm and Support Vector Machine

  • Author

    Ahmed, Saleh ; Islam, Md Rafiqul ; Azam, Md Shafiul

  • Author_Institution
    Dept. of CSE, Leading Univ., Sylhet, Bangladesh
  • fYear
    2009
  • fDate
    21-23 Dec. 2009
  • Firstpage
    390
  • Lastpage
    393
  • Abstract
    This paper presents Bangla numeral character recognition system using supervised locally linear embedding algorithm and support vector machine (SVM). The locally linear embedding (LLE) algorithm is an unsupervised technique proposed for nonlinear dimensionality reduction. In this paper, we describe its supervised variant (SLLE). Where class membership information is used to map overlapping high dimensional data into disjoint clusters in the embedded space. we combined it with support vector machine (SVM) for classifying handwritten digits from the on-line handwritten Bangla numeral database.
  • Keywords
    handwritten character recognition; image classification; natural language processing; support vector machines; unsupervised learning; Bangla hand written digit recognition; Bangla numeral character recognition system; class membership information; handwritten digit classification; nonlinear dimensionality reduction; online handwritten Bangla numeral database; supervised locally linear embedding algorithm; support vector machine; unsupervised technique; Character recognition; Clustering algorithms; Embedded computing; Handwriting recognition; Image databases; Image recognition; Information technology; Nearest neighbor searches; Support vector machine classification; Support vector machines; Bangla Handwritten; Digit Recognition; LLE; SLLE; SVM;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computers and Information Technology, 2009. ICCIT '09. 12th International Conference on
  • Conference_Location
    Dhaka
  • Print_ISBN
    978-1-4244-6281-0
  • Type

    conf

  • DOI
    10.1109/ICCIT.2009.5407269
  • Filename
    5407269