• 제목/요약/키워드: HPDAF (Highest Probabilistic Data Association Filter)

검색결과 1건 처리시간 0.013초

적외선 영상 표적추적 성능 개선을 위한 적응적인 자동문턱치 산출 기법 연구 (Adaptive Automatic Thresholding in Infrared Image Target Tracking)

  • 김태한;송택렬
    • 제어로봇시스템학회논문지
    • /
    • 제17권6호
    • /
    • pp.579-586
    • /
    • 2011
  • It is very critical for image processing of IIR (Imaging Infrared) seekers to achieve improved guidance performance for missile systems to determine appropriate thresholds in various environments. In this paper, we propose automatic threshold determination methods for proper thresholds to extract definite target signals in an EOCM (Electro-Optical Countermeasures) environment with low SNR (Signal-to-Noise Ratios). In particular, thresholds are found to be too low to extract target signals if one uses the Otsu method so that we suggest a Shifted Otsu method to solve this problem. Also we improve extracting target signal by changing Shifted Otsu thresholds according to the TBR (Target to Background Ratio). The suggested method is tested for real IIR images and the results are compared with the Otsu method. The HPDAF (Highest Probabilistic Data Association Filter) which selects the target originated measurements by taking into account of both signal intensity and statistical distance information is applied in this study.