Proceedings Paper
Optical correlation filters for large-class OCR applications| Format | Member Price | Non-Member Price |
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Paper Abstract
The performance of two new optical correlation filters (G-MACE and MINACE) for large class (many fonts and true class words) OCR (optical character recognition) applications is considered. We consider filters that can recognize many key words in upper case (UC) and mixed case (MC) and various point sizes in the presence of OCR scanner sampling errors. New results are presented and guidelines for large class filters are advanced.
Paper Details
Date Published: 1 August 1991
PDF: 12 pages
Proc. SPIE 1470, Data Structures and Target Classification, (1 August 1991); doi: 10.1117/12.44852
Published in SPIE Proceedings Vol. 1470:
Data Structures and Target Classification
Vibeke Libby, Editor(s)
PDF: 12 pages
Proc. SPIE 1470, Data Structures and Target Classification, (1 August 1991); doi: 10.1117/12.44852
Show Author Affiliations
David P. Casasent, Carnegie Mellon Univ. (United States)
Anand K. Iyer, Carnegie Mellon Univ. (United States)
Anand K. Iyer, Carnegie Mellon Univ. (United States)
Srinivasan Gopalaswamy, Carnegie Mellon Univ. (United States)
Published in SPIE Proceedings Vol. 1470:
Data Structures and Target Classification
Vibeke Libby, Editor(s)
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