On virtual partitioning of large dictionaries for contextual post-processing to improve character recognition

A new approach to the partitioning of large dictionaries by virtual views is presented. The basic idea is that additional knowledge sources of text recognition and text analysis are employed for fast dictionary look-up in order to prune the search space through static or dynamic views. The heart of the system is a redundant hashing technique which involves a set of hash functions dealing with noisy input efficiently. Currently, the system is composed of two main system components: the dictionary generator and the dictionary controller. While the dictionary generator initially builds the system by using profiles and source dictionaries, the controller allows the flexible integration of different search heuristics. Results prove that the system achieves a respectable speed-up of dictionary access time