• DocumentCode
    498320
  • Title

    The Optimized Design and Application of Circular Morphological Filter

  • Author

    Hong, Che ; Longhe, Sun

  • Author_Institution
    No. 613 Inst. of the China Aviation Ind., Luoyang, China
  • Volume
    3
  • fYear
    2009
  • fDate
    19-21 May 2009
  • Firstpage
    257
  • Lastpage
    261
  • Abstract
    With an optimized structure, morphological filter is more effective to detect moving spot target in infrared image sequences. Based on the real convex figure, morphological filter with circular structure is designed in this paper. The neural network is introduced to optimize the filter element. The adaptive detection threshold is built based on the statistical characters. Experimental results to real data show that the detection probability of images (SNRap2) can reach more than 98% with 1% false alarm with the optimized circular morphological filter, which detection probability is better than that with fixed element morphological filter and square morphological filter.
  • Keywords
    image sequences; neural nets; object detection; statistical analysis; adaptive detection threshold; circular morphological filter; circular structure; image detection probability; infrared image sequences; morphological filter; neural network; optimized design; statistical characters; Design optimization; Geometrical optics; Image processing; Infrared detectors; Infrared imaging; Neural networks; Object detection; Optical filters; Optical sensors; Probability; Morphological filter; circular element; neural network;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Systems, 2009. GCIS '09. WRI Global Congress on
  • Conference_Location
    Xiamen
  • Print_ISBN
    978-0-7695-3571-5
  • Type

    conf

  • DOI
    10.1109/GCIS.2009.119
  • Filename
    5209161