A Semi-incremental Recognition Method for On-Line Handwritten English Text

This paper presents a semi-incremental recognition method for online handwritten English text. We employ local processing strategy and focus on a recent sequence of strokes defined as "scope". For the latest scope, we build and update a segmentation and recognition candidate lattice and advance the best-path search incrementally. We utilize the result of the best-path search in the previous scope to exclude unnecessary segmentation candidates. This reduces the number of candidate word recognition with the result of reduced processing time. We also reuse the segmentation and recognition candidate lattice in the previous scope for the latest scope. Moreover, triggering recognition processes every few strokes save CPU time. Experiment made on IAM-OnDB database shows the effectiveness of the proposed method not only in reduced processing time and waiting time, but also in recognition accuracy.