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Effect of sensor-target-background distance on target tracking using a fly eye sensor.

Arif Khan1, Robert W Streeter, Cameron H G Wright

  • 1University of Wyoming, Laramie.

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A biomimetic fly eye sensor shows promise for edge detection. Optimizing its use for object tracking requires careful consideration of target and background distances, which can be mitigated with a low-pass filter.

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Area of Science:

  • Biomimetic sensor technology
  • Computational vision systems
  • Image processing applications

Background:

  • The Wyoming Image and Signal Processing Research (WISPR) Laboratory developed a multi-aperture optical sensor inspired by the housefly's visual system.
  • This fly eye sensor demonstrates effective edge detection across various contrast levels with low processing demands.
  • Potential applications include fast motion detection and object tracking, necessitating further optimization studies.

Purpose of the Study:

  • To analyze the impact of background and target distances on the fly eye sensor's performance.
  • To investigate potential ambiguities and performance degradation in tracking systems.
  • To evaluate mitigation strategies for distance-related sensor response variations.

Main Methods:

  • Computer simulation of the fly eye sensor using MATLAB.
  • Analysis of sensor response with varying target and background distances.
  • Evaluation of a low-pass filter's effectiveness in mitigating distance-induced effects.

Main Results:

  • Sensor response is significantly affected by the relative placement of the target and background.
  • Placing the target closer to the sensor and further from the background influences the sensor's output.
  • A properly designed low-pass filter can substantially reduce performance ambiguities caused by distance variations.

Conclusions:

  • The distance between the target and background is a critical factor for accurate fly eye sensor-based tracking.
  • Failure to account for these distance effects can lead to performance degradation and tracking errors.
  • Low-pass filtering offers an effective method to mitigate these issues while maintaining acceptable sensor response.