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This paper proposes a method for handwritten Chinese/Japanese text (character string) recognition based on semi-Markov conditional random fields (semi-CRFs). The high-order semi-CRF model is defined on a lattice containing all possible segmentation-recognition hypotheses of a string to elegantly fuse the scores of candidate character recognition and the compatibilities of geometric and linguistic...
Handwritten text recognition systems commonly combine character classification confidence scores and context models for evaluating candidate segmentation-recognition paths, and the classification confidence is usually optimized at character level. On comparing the performance of class-dependent and class-independent confidence transformation (CT), this paper proposes two regularized class-dependent...
In keyword spotting from handwritten documents, the word similarity is usually computed by combining character similarities. Converting similarity to probabilistic confidence is beneficial for context fusion and threshold selection. In this paper, we propose to directly estimate the posterior probability of candidate characters based on the N-best paths from the segmentation-recognitioin candidate...
This paper introduces a pair of online and offline Chinese handwriting databases, containing samples of isolated characters and handwritten texts. The samples were produced by 1,020 writers using Anoto pen on papers for obtaining both online trajectory data and offline images. Both the online samples and offline samples are divided into six datasets, three for isolated characters (DB1.0-C1.2) and...
Real-time recognition of handwritten sentences enables fast text input but the dynamic nature of writing makes reliable text line segmentation difficult. This paper proposes a method for real-time dynamic text line segmentation of online Chinese handwriting. The core of the method is a statistical classifier for modeling the geometric relationship between an ongoing stroke and the previous text lines,...
In the Chinese handwriting recognition competition organized with the ICDAR 2011, four tasks were evaluated: offline and online isolated character recognition, offline and online handwritten text recognition. To enable the training of recognition systems, we announced the large databases CASIA-HWDB/OLHWDB. The submitted systems were evaluated on un-open datasets to report character-level correct rates...
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