Optical processing of wire-frame models for object recognition

Samuel Peter Kozaitis; Rufus H. Cofer

doi:10.1117/12.44883

1 August 1991 Optical processing of wire-frame models for object recognition

Proceedings Volume 1471, Automatic Object Recognition; (1991) https://doi.org/10.1117/12.44883
Event: Orlando '91, 1991, Orlando, FL, United States

Abstract

Imagery from actual sensors was used for automatic object recognition with a binary phase- only filtering (BPOF) optical correlator. The correlator was primarily tested for applications that involve objects with a nonrepeatable signature. Digital image processing techniques were used to threshold gray-level images and approximate their boundaries with polygons to limit variations of input imagery before correlation. Correlation responses increased and worked best when relatively short line segments were used in the approximation. The best results were obtained when a convex polygon was drawn to the outward-most points of the object. This is equivalent to extracting specific shape features of the object. The method presented here reduced the sensitivity of a BPOF to changes in an object's appearance when an object varied in different or unknown ways.

Citation Download Citation

Samuel Peter Kozaitis and Rufus H. Cofer "Optical processing of wire-frame models for object recognition", Proc. SPIE 1471, Automatic Object Recognition, (1 August 1991); https://doi.org/10.1117/12.44883

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