کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
531537 869853 2008 13 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Writer identification of Chinese handwriting documents using hidden Markov tree model
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر چشم انداز کامپیوتر و تشخیص الگو
پیش نمایش صفحه اول مقاله
Writer identification of Chinese handwriting documents using hidden Markov tree model
چکیده انگلیسی

Handwriting-based writer identification, a branch of biometrics, is an active research topic in pattern recognition. Since most existing methods and models aim to on-line and/or text-dependent writer identification, it is necessary to propose new methods for off-line, text-independent writer identification. At present, two-dimensional Gabor model is widely acknowledged as an effective and classic method for off-line, text-independent handwriting identification, while it still suffers from some inherent shortcomings, such as the excessive calculational cost. In this paper, we present a novel method based on hidden Markov tree (HMT) model in wavelet domain for off-line, text-independent writer identification of Chinese handwriting documents. Our experiments show this HMT method, compared with two-dimensional Gabor model, not only achieves better identification results but also greatly reduces the elapsed time on computation.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Pattern Recognition - Volume 41, Issue 4, April 2008, Pages 1295–1307
نویسندگان
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