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Probe-based automatic target recognition in infrared imagery.

S Z Der1, R Chellappa

  • 1Night Vision Electronic Sensors Directorate, AMSEL-RD-NV-VISP-LET, Ft. Belvoir, VA.

IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society
|January 1, 1997
PubMed
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This study introduces a novel probe-based method for target recognition in forward-looking infrared (FLIR) imagery. The approach effectively utilizes image modeling and 3-D CAD data for accurate target detection in infrared images.

Area of Science:

  • Computer Vision
  • Image Processing
  • Infrared Imaging

Background:

  • Target recognition in forward-looking infrared (FLIR) imagery presents challenges due to environmental factors and sensor limitations.
  • Existing methods often struggle with precise localization and identification of targets in complex scenes.

Purpose of the Study:

  • To develop and validate a probe-based approach for robust target recognition in single-frame FLIR imagery.
  • To integrate image modeling with 3-D computer-aided design (CAD) data for enhanced target shape analysis.

Main Methods:

  • A probe-based method employing mathematical functions to analyze local pixel values in FLIR images.
  • Estimation of empirical probability density functions for probe values to determine target presence likelihood.

Related Experiment Videos

  • Utilizing 3-D CAD models for target shape information and applying a generalized likelihood ratio test for hypothesis testing.

    • Main Results:

    • The developed algorithm demonstrated effective target recognition capabilities on both real and synthetic FLIR datasets.
    • The probe-based approach successfully estimated target poses and distinguished targets from background clutter.
    • Quantitative and qualitative experimental results validated the efficacy of the proposed image model and recognition algorithm.

    Conclusions:

    • The probe-based approach combined with image modeling offers a powerful tool for target recognition in FLIR imagery.
    • This method provides a robust framework for analyzing infrared images, leveraging both local pixel information and global shape priors.
    • The study highlights the potential of this technique for various applications requiring accurate object detection in infrared sensing.