• DocumentCode
    1749104
  • Title

    A biological model for distortion-invariant target recognition

  • Author

    Iftekharuddin, Khan M. ; Power, Gregory

  • Author_Institution
    Electr. & Comput. Eng., Univ. of Memphis, TN, USA
  • Volume
    1
  • fYear
    2001
  • fDate
    2001
  • Firstpage
    559
  • Abstract
    The premise of this proposal can be characterized by a novel direction of thinking outside of the usual automatic target recognition (ATR) paradigm that primarily involves a working set of algorithms based on known engineering principles. Contemporary knowledge of the human visual system is analyzed to draw insights and thereby to rethink our simulated ATR environment. The vision system of primates that involves the retina as a sensor and the primary visual cortex as a major information processing organ offers a unique opportunity to gain understanding of the biological ATR process. We attempt to implement a distortion invariant ATR system based on such biological inspiration
  • Keywords
    infrared imaging; neural nets; object recognition; physiological models; visual perception; biological model; distortion-invariant target recognition; human visual system; primates; retina; vision system; Analytical models; Biological system modeling; Biosensors; Brain modeling; Humans; Machine vision; Proposals; Retina; Target recognition; Visual system;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks, 2001. Proceedings. IJCNN '01. International Joint Conference on
  • Conference_Location
    Washington, DC
  • ISSN
    1098-7576
  • Print_ISBN
    0-7803-7044-9
  • Type

    conf

  • DOI
    10.1109/IJCNN.2001.939083
  • Filename
    939083