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This paper describes an online handwritten Japanese character string recognition system integrating scores of geometric context, character recognition, and linguistic context. We give a string evaluation criterion for better integrating the multiple scores while overcoming the effect of string length variability. For measuring geometric context, we propose(More)
Nonlinear normalization (NLN) based on line density equalization has been widely used in handwritten Chinese character recognition (HCCR). Our previous results showed that global transformation methods, including moment normalization and a newly proposed bi-moment method, generate smooth normalized shapes at lower computation effort while yielding(More)
The performance of handwritten numeral string recognition integrating segmentation and classification relies on the classification accuracy and the resistance to non-characters of the underlying classifier. The classifier can be trained at either character level (with character and non-character samples) or string level (with string samples). We show that(More)
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(More)