On partitioning a dictionary for visual text recognition

This paper has used word-length, word-envelope, character combination and a combination of these as the basis of partitioning the dictionary, and considered approximately 10,000 of the most frequently used words for analysis and comparison.

Abstract

In this paper we examine some of the possible ways of partitioning a dictionary in the context of visual text recognition. We have considered approximately 10,000 of the most frequently used words for our analysis and comparison. We have used word-length, word-envelope, character combination and a combination of these as the basis of partitioning the dictionary. These features do not require additional computation as they are mostly available as a by-product of the on-going process of character recognition. In all, 11 different schemes have been examined and evaluated with respect to real-life problems faced in text recognition.