Optimization of OT-MACH filter generation for target recognition

Oliver C. Johnson; Weston Edens; Thomas T. Lu; Tien-Hsin Chao

doi:10.1117/12.820950

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13 April 2009 Optimization of OT-MACH filter generation for target recognition

Oliver C. Johnson, Weston Edens, Thomas T. Lu, Tien-Hsin Chao

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Proceedings Volume 7340, Optical Pattern Recognition XX; 734008 (2009) https://doi.org/10.1117/12.820950
Event: SPIE Defense, Security, and Sensing, 2009, Orlando, Florida, United States

Abstract

An automatic Optimum Trade-off Maximum Average Correlation Height (OT-MACH) filter generator for use in a gray-scale optical correlator (GOC) has been developed for improved target detection at JPL. While the OT-MACH filter has been shown to be an optimal filter for target detection, actually solving for the optimum is too computationally intensive for multiple targets. Instead, an adaptive step gradient descent method was tested to iteratively optimize the three OT-MACH parameters, α, β, and γ. The feedback for the gradient descent method was a composite of the performance measures, correlation peak height and peak to side lobe ratio. The automated method generated and tested multiple filters in order to approach the optimal filter quicker and more reliably than the current manual method. Initial usage and testing has shown preliminary success at finding an approximation of the optimal filter, in terms of α, β, γ values. This corresponded to a substantial improvement in detection performance where the true positive rate increased for the same average false positives per image.

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Oliver C. Johnson, Weston Edens, Thomas T. Lu, and Tien-Hsin Chao "Optimization of OT-MACH filter generation for target recognition", Proc. SPIE 7340, Optical Pattern Recognition XX, 734008 (13 April 2009); https://doi.org/10.1117/12.820950

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