• DocumentCode
    720701
  • Title

    Automatic target recognition by infrared and visible image matching

  • Author

    Kai-Sheng Cheng ; Huei-Yung Lin

  • Author_Institution
    Dept. of Electr. Eng., Nat. Chung Cheng Univ., Chiayi, Taiwan
  • fYear
    2015
  • fDate
    18-22 May 2015
  • Firstpage
    312
  • Lastpage
    315
  • Abstract
    Automatic target recognition based on the long wave infrared (LIR) and visible-light spectrum (VIS) image matching is a very challenging problem. It is due to the fact that the images between LIR and VIS have lots of different textures. This difficulty is inherent in the thermal radiation imaging affected by one of the principal mechanisms so called heat transfer. In this paper, a novel algorithm is presented for object recognition between the LIR and VIS images under various conditions. It is assumed that the visible light images of the target are available a priori, and the newly acquired infrared images are used to perform the target recognition task. The LIR and VIS images are first initialized with edge detection and binary template matching, followed by a local fuzzy threshold to identify the high similarity objects. Our method has has low computational requirements and can be implemented on a real-time system. Several experiments are carried out using the real scene images with various test objects.
  • Keywords
    edge detection; fuzzy set theory; heat radiation; heat transfer; image matching; infrared imaging; object recognition; optical images; visible spectra; LIR image matching; VIS image matching; automatic target recognition; binary template matching; edge detection; heat transfer; image textures; long wave infrared image matching; object recognition; thermal radiation imaging; visible light spectrum image matching; Cameras; Feature extraction; Image edge detection; Missiles; Target recognition; Video sequences;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Machine Vision Applications (MVA), 2015 14th IAPR International Conference on
  • Conference_Location
    Tokyo
  • Type

    conf

  • DOI
    10.1109/MVA.2015.7153193
  • Filename
    7153193