Distortion-invariant optical filter sets for large-class problems: OCR case study

David P. Casasent

doi:10.1117/12.57042

1 February 1992 Distortion-invariant optical filter sets for large-class problems: OCR case study

David P. Casasent

Proceedings Volume 1607, Intelligent Robots and Computer Vision X: Algorithms and Techniques; (1992) https://doi.org/10.1117/12.57042
Event: Robotics '91, 1991, Boston, MA, United States

Abstract

An OCR machine printed problem is selected as an example of a large class pattern recognition problem. We consider discrimination of alpha and numeric fields, recognition of all numbers, recognition of key words (street suffixes, personal titles), state/city/street names, etc. These operations are performed on destination address blocks (DABs) in the face of numerous variations in the type face (laser writer, dot matrix, typewriter, etc.), font, data drop out (due to printing errors), point size, +/- 5 degree(s) rotations, etc. An optical correlator with banks of distortion invariant hierarchical/inference filters appears to be an ideal adjunct to other OCR techniques (AI, parsing, context, use of lexicons, etc.).

Citation Download Citation

David P. Casasent "Distortion-invariant optical filter sets for large-class problems: OCR case study", Proc. SPIE 1607, Intelligent Robots and Computer Vision X: Algorithms and Techniques, (1 February 1992); https://doi.org/10.1117/12.57042

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