초록 ▼

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 repre

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.

대표청구항 ▼

[ I claim:] [1.] In a system for classifying symbols in image data, said image data representing an image, a method for merging equivalence classes to create a consolidated equivalence class, said method comprising the steps of:a) classifying symbols extracted from image data to create a plurality o

[ I claim:] [1.] In a system for classifying symbols in image data, said image data representing an image, a method for merging equivalence classes to create a consolidated equivalence class, said method comprising the steps of:a) classifying symbols extracted from image data to create a plurality of equivalence classes, each of said equivalence classes having an exemplar representing the equivalence class;b) matching a first equivalence class exemplar to a second equivalence class exemplar, said matching step using endpoint ranges derived from one of run endpoints of the first equivalence class exemplar and run endpoints of the second equivalence class exemplar;c) if said first equivalence class exemplar and said second equivalence class exemplar match, combining said first equivalence class and said second equivalence class exemplar to create a consolidated equivalence class;d) repeating step b)-c) for each of said plurality of equivalence classes to create a plurality of consolidated equivalence classes; ande) for each of said plurality of consolidated equivalence classes, selecting an exemplar from a set of exemplars used to create said consolidated equivalence class, to represent said consolidated equivalence class.