NDLI: An improved feature extraction method for individual offline handwritten digit recognition

Content Provider	IEEE Xplore Digital Library
Author	Wang Qinghui Yang Aiping Dai Wenzhan
Copyright Year	2010
Description	Author affiliation: Department of Automatic Control, Zhejiang Sci-Tech University, Hangzhou, 310018, China (Wang Qinghui; Dai Wenzhan) \|\| Zhejiang University of Finance & Economics Hangzhou, 310018, China (Yang Aiping)
Abstract	Offline handwritten digit recognition (OHDR) is considered as one of difficult problems in the field of pattern recognition. Because it is a challenging computational problem mainly due to the vast differences associated with the handwritten patterns of different individuals. In this paper, a novel method of feature extraction is presented based on structural feature for OHDR by simulating the process of human recognizing handwritten digit. Firstly state and state value are introduced, then the steps of how to determine the eigenvalue is explained in detail, last the method is applied in OHDR, and the result show its effectiveness.
Starting Page	6327
Ending Page	6330
File Size	562577
Page Count	4
File Format	PDF
ISBN	9781424467129
e-ISBN	9781424467129
DOI	10.1109/WCICA.2010.5554355
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-07-07
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Eigenvalues and eigenfunctions Feature extraction Character recognition Handwriting recognition Data mining Algorithm design and analysis feature extraction Offline handwritten digit recognition
Content Type	Text
Resource Type	Article

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