Abstract
This paper describes a method of on-line handwritten Japanese text recognition by improved path evaluation. Based on a theoretical ground, the method evaluates the likelihood of candidate segmentation paths by combining scores of character pattern size, inner gap, character recognition, single and pair character position, candidate segmentation point and linguistic context, with the weight parameters optimized by a genetic algorithm. The path score is insensitive to the number of candidate patterns and the optimal path can be found by Viterbi search. Experimental results demonstrate the superiority of the proposed method.
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