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ICDAR
2011
IEEE

OCR-Driven Writer Identification and Adaptation in an HMM Handwriting Recognition System

12 years 9 months ago
OCR-Driven Writer Identification and Adaptation in an HMM Handwriting Recognition System
—We present an OCR-driven writer identification algorithm in this paper. Our algorithm learns writer-specific characteristics more precisely from explicit character alignment using the Viterbi algorithm and shows significant reduction of close-set writer identification error rates, compared with the GMM-based method. With writers’ identities retrieved, we improve the performance of handwriting recognition using the HMM trained adapted on the training data of that writer. In our system, writer identification and OCR are highly interactive. They improve the performance of each other and thus show close approximation of supervised text-dependent writer identification and writer-dependent HMM handwriting. Keywords- Handwriting recognition, writer identification, hidden markov model 12
Huaigu Cao, Rohit Prasad, Prem Natarajan
Added 24 Dec 2011
Updated 24 Dec 2011
Type Journal
Year 2011
Where ICDAR
Authors Huaigu Cao, Rohit Prasad, Prem Natarajan
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