A Fast Search Technique for Large Vocabulary On-line Handwriting Recognition

Abstract

State-of-the-art on-line handwriting recognition systems should be able to handle dictionary sizes of at least 25,000 words or more to be useful for real-world applications. Using dictionaries of this size requires fast search techniques to achieve reasonable recognition times. In this paper we present a search approach yielding recognition times, which are virtually independent of the dictionary size. This approach combines a tree representation of the dictionary with efficent pruning techniques to reduce the search space without loosing much recognition performance compared to a flat exhaustive search through all words in the dictionary. The tree search with pruning is about 15 times faster than a flat search and allows us to run the NPen++ on-line handwriting recognition system in real-time with dictionary sizes up to 100,000 words.