On-line cursive script recognition using an island-driven search technique

Abstract

A new approach for on-line cursive script recognition that combines a letter spotting technique with an island-driven lattice search algorithm is presented. Initially, all plausible letter components within an input pattern are detected, using a letter spotting technique based on hidden Markov models. A word hypothesis lattice is generated as a result of the letter spotting. Then an island-driven search algorithm is performed to find the optimal path on the word hypothesis lattice, which corresponds to the most probable word among the dictionary words. The results of this experiment suggest that the proposed method works effectively in recognizing English cursive words. In a word recognition test, the average 85.4% word accuracy was obtained.