• DocumentCode
    2778789
  • Title

    Object Recognition using image descriptors

  • Author

    Mohan, V. ; Shanmugapriya, P. ; Venkataramani, Y.

  • Author_Institution
    Saranathan Coll. of Eng., Trichy
  • fYear
    2008
  • fDate
    18-20 Dec. 2008
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    Patten recognition techniques are often an important component of intelligent systems to describe, classify and recognise the objects. Object recognition using linear vector quantization neural network which is trained using descriptors such as boundary and regional descriptors is presented in this paper. Out of the various descriptors available, a combination of these descriptors extracted from the input patterns is proposed for recognizing objects using a vector quantization neural network. The feature vector obtained from the object is the combination of a boundary descriptor, the signature or and a regional descriptor, the Zernike moment magnitudes of the image. The results of the testing phase are included at the end of this paper.
  • Keywords
    Zernike polynomials; feature extraction; image classification; learning (artificial intelligence); neural nets; object recognition; quantisation (signal); Zernike moment magnitude; boundary descriptor; feature extraction; image descriptor; intelligent system; linear vector quantization neural network training; object classification; object recognition; patten recognition; regional descriptor; signature descriptor; Data mining; Educational institutions; Feature extraction; Image recognition; Neural networks; Object recognition; Pattern classification; Pattern recognition; Testing; Vector quantization; Classification; Descriptors; Object Recognition; Signature; Zernike Moment;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computing, Communication and Networking, 2008. ICCCn 2008. International Conference on
  • Conference_Location
    St. Thomas, VI
  • Print_ISBN
    978-1-4244-3594-4
  • Electronic_ISBN
    978-1-4244-3595-1
  • Type

    conf

  • DOI
    10.1109/ICCCNET.2008.4787717
  • Filename
    4787717