Consolidation of equivalence classes of scanned symbols

Details Consolidation of equivalence classes of scanned symbols Consolidation of equivalence classes of scanned symbols

1995-12-20

1998-10-06

Shalwala, Bipin

Image analysis

Pattern recognition

Classification

382190, 382226, 382227, 382245, G06K 962, G06K 968, G06K 970, G06K 946

Patent

active

058189653

ABSTRACT:
A method and apparatus for consolidation of equivalence classes of scanned symbols as may be used for image data compression. The present invention performs run-length symbol extraction and classifies symbols based on both horizontal and vertical run length information. An equivalence class is represented by an exemplar. Feature-based classification criteria for matching an exemplar is defined by a corresponding exemplar template. The feature-based classification criteria all use quantities that can be readily computed from the run endpoints. Reducing the number of equivalence classes is achieved through a process called equivalence class consolidation. Equivalence class consolidation utilizes the symbol classifier to identify matched exemplars indicating equivalence classes which may be merged. For a consolidated equivalence class, the exemplar matching the most symbols is selected as the representative for the class.

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Huttenlocher, D.P., Klanderman, G.A., and Rucklidge, W.J., "Comparing Images Using the Hausdorff Distance," Research Report for Department of Computer Science, Cornell University, Ithaca, N.Y., 1991.
Huttenlocher, D.P., Rucklidge, W.J., "A Multi-Resolution Technique for Comparing Images Using the Hausdorff Distance," Research Report for Department of Computer Science, Cornell Unitersity, Ithaca, N.Y., 1992.

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