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This paper describes a new document retrieval method that is tolerant of OCR segmentation errors in document images. To overcome the segmentation and recognition errors that most OCR-based retrieval systems suffer from, the proposed method consists of two processing phases. First, the OCR engine first generates multiple character-segmentation and recognition hypotheses. Then the retrieval engine extracts keywords from the recognition hypotheses by using lexicon-driven dynamic programming (DP) matching. We have applied this method to both handwritten and printed document images and have demonstrated its effectiveness in reducing false drops and false alarms.
Date of Conference: 26-29 Oct. 2004