1 April 1992 Performance of synthetic discriminant functions for binary phase-only filtering of thresholded imagery
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Abstract
Imagery from infrared sensors was used for automatic object recognition using a digital simulation of an optical correlator with binary phase-only filters (BPOFs). The method was tested primarily for applications that involve objects with a nonrepeatable signature. In imagery from actual sensors, object boundaries can be poorly defined, and the same object can vary in shape significantly, depending on a host of variables. Digital image processing techniques were used to threshold gray-level images before correlation so that variations due to environmental conditions and other variables can be limited. A synthetic discriminant function made from a training set of thresholded imagery was used to create BPOFs. The potential of the recognition method was evaluated with imagery that varied in an unknown or nonrepeatable manner. The method presented here reduced the sensitivity of a BPOF to changes in an object's appearance when the object varied in an unknown way.
Samuel Peter Kozaitis, Wesley E. Foor, "Performance of synthetic discriminant functions for binary phase-only filtering of thresholded imagery," Optical Engineering 31(4), (1 April 1992). https://doi.org/10.1117/12.56116 . Submission:
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