Paper
3 September 1993 Target detection using image motion error measure
James L. Wayman, John M. Libert, Thomas R. Tsao
Author Affiliations +
Abstract
The spatio-temporal constraint equation for computation of the optical flow holds only over local spatio-temporal regions where motion is translational with constant velocity or over non- moving background regions where the image velocity is zero. Where the expression is true, it is possible to estimate the image motion vector of local image regions by minimizing the squared error over the local region. The expression is not true in the moving boundaries of moving objects over a stationary background, over regions with multiple moving objects, or over objects not in purely translational motion. Under these conditions, the accurate computation of motion vectors is not possible using this method. However, the error squared term, itself, may be used as a moving target indicator able to segment moving targets from noise and background clutter. This paper proposes and assesses the feasibility of using the error measure to detect moving boundaries in high noise images. We assess the performance of this error-squared measure in localizing object motion in high noise environments for two filtering functions G(x,y): the Gaussian function and the Gabor function.
© (1993) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
James L. Wayman, John M. Libert, and Thomas R. Tsao "Target detection using image motion error measure", Proc. SPIE 1955, Signal Processing, Sensor Fusion, and Target Recognition II, (3 September 1993); https://doi.org/10.1117/12.154984
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CITATIONS
Cited by 3 scholarly publications.
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KEYWORDS
Motion measurement

Signal to noise ratio

Convolution

Error analysis

Gaussian filters

Image filtering

Image segmentation

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