Scalable hash-based character recognition

Abstract

The subject invention leverages a scalable character glyph hash table to provide an efficient means to identify print characters where the character glyphs are identical over independent presentation. The hash table allows for quick determinations of glyph meta data as, for example, a pre-filter to traditional OCR techniques. The hash table can be trained for a particular environment, user, language, character set (e.g., alphabet), document type, and/or specific document and the like. This permits substantial flexibility and increases in speed in identifying unknown glyphs. The hash table itself can be composed of single or multiple tables that have a specific optimization purpose. In one instance of the subject invention, traditional OCR techniques can be utilized to update the hash tables as needed based on glyph frequency. This keeps the hash tables from growing by limiting updates that reduce its performance, while adding frequently determined glyphs to increase the pre-filter performance.