NDLI: HMM-Based Off-Line Handwritten Chinese Characters Recognition Using Krawtchouk Moments

Content Provider	IEEE Xplore Digital Library
Author	Xianmei Wang Yang Yang Bin Xie Hong Wang
Copyright Year	2006
Description	Author affiliation: Dept. of Electron. Inf. Eng., Univ. of Sci. & Technol., Beijing (Xianmei Wang; Yang Yang; Bin Xie; Hong Wang)
Abstract	This paper proposes a new efficient approach using the set of Krawtchouk moments and HMM for character recognition. The Krawtchouk moments set is a new set of orthogonal moments based on the discrete classical Krawtchouk polynomials. Compared to continuous moments such as geometric, Hu invariants, Zernike and Legendre moments, the implementation of Krawtchouk moments doesn't involve any numerical approximation and coordinates transform, since the basis set is orthogonal in the discrete domain of the image coordinates space. This property makes Krawtchouk moments superior to the conventional continuous moments. In character recognition field, HMM is a good solution because of its strong adaptive to the written deforming. In this paper, Krawtchouk moments and HMM are combined to recognize off-line handwritten legal amount. Experiments confirm the performance of our proposed methods. The average recognition is much higher than Legendre moments and Hu invariants under HMM framework
Starting Page	10068
Ending Page	10072
File Size	221649
Page Count	5
File Format	PDF
ISBN	1424403324
DOI	10.1109/WCICA.2006.1713969
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2006-06-21
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Hidden Markov models Character recognition Paper technology Polynomials Discrete transforms Handwriting recognition Law Legal factors Intelligent control Automation Discrete Orthogonal moments Character Recognition Krawtchouk Moments HMM
Content Type	Text
Resource Type	Article

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