Combining diverse systems for handwritten text line recognition
نویسندگان
چکیده
منابع مشابه
Combining diverse on-line and off-line systems for handwritten text line recognition
The machine replication of human reading has been the subject of intensive research for more than three decades. A large number of research papers and reports have already been published on this topic. Many commercial establishments have manufactured recognizers of varying capabilities. Handheld, desk-top, medium-size and large systems costing as high as half a million dollars are available, an...
متن کاملSelf-training for Handwritten Text Line Recognition
Off-line handwriting recognition deals with the task of automatically recognizing handwritten text from images, for example from scanned sheets of paper. Due to the tremendous variations of writing styles encountered between different individuals, this is a very challenging task. Traditionally, a recognition system is trained by using a large corpus of handwritten text that has to be transcribe...
متن کاملCombining On-Line and Off-Line Bidirectional Long Short-Term Memory Networks for Handwritten Text Line Recognition
In this paper we present a multiple classifier system (MCS) for on-line handwriting recognition. The MCS combines several individual recognition systems based on bidirectional long short-term memory networks. To obtain diverse recognizers, we use different feature sets based on on-line and off-line features. Furthermore, we generate a number of different recognizers by changing the initializati...
متن کاملEnsemble methods for offline handwritten text line recognition
This thesis investigates ensemble methods for offline recognition of English handwritten text lines. Multiple recognisers are automatically generated from a single base recognition system. Combining the output of these multiple recognisers provides the final ensemble result. The underlying recognisers are based on hidden Markov models. One model is built for each character. Based on the lexicon...
متن کاملRejection strategies for offline handwritten text line recognition
This paper investigates rejection strategies for unconstrained offline handwritten text line recognition. The rejection strategies depend on various confidence measures that are based on alternative word sequences. The alternative word sequences are derived from specific integration of a statistical language model in the hidden Markov model based recognition system. Extensive experiments on the...
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ژورنال
عنوان ژورنال: Machine Vision and Applications
سال: 2009
ISSN: 0932-8092,1432-1769
DOI: 10.1007/s00138-009-0208-9