Optical EngineeringStatistical filtering of time-sequenced peak correlation responses for distortion invariant recognition of multiple input objects
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A distortion invariant correlation plane filter (DICPF) based on the analysis of variance technique used in experimental statistics is used to analyze peak correlation responses from a time sequenced coherent optical correlator and identify multiple input objects rapidly. A mathematical development of the filter for invariance to an arbitrary number of distortions, such as rotation, scale, aspect, or any other distortion that can be quantized, is presented. This statistical correlation plane filtering technique can be used to process output correlation data from an array of simple or composite filters that are presented either sequentially or simultaneously (space multiplexed at the Fourier plane of a coherent optical correlator). Results are presented from computer simulations and experiments using time sequenced simple binary phase-only reference filters (BPOFs) to achieve rotation and scale invariant recognition of multiple objects. Results from experiments using sequences of composite BPOFs that are invariant over a range of target rotations are also presented to demonstrate the general applicability of this technique. These results indicate that the DICPF can correctly identify multiple objects within the correlator's target group more than 90% of the time, even in the presence of clutter and noise (up to 20% noise), while maintaining a false alarm rate of 6% or less using single BPOFs.