Polar transformation system for offline handwritten character recognition

Wang, Xianjing and Sajjanhar, Atul 2011, Polar transformation system for offline handwritten character recognition, in Software engineering, artificial intelligence, networking and parallel/distributed computing 2011, Springer, Berlin, Germany, pp.15-24.

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Title Polar transformation system for offline handwritten character recognition
Author(s) Wang, Xianjing
Sajjanhar, Atul
Title of book Software engineering, artificial intelligence, networking and parallel/distributed computing 2011
Editor(s) Lee, Roger
Publication date 2011
Series Studies in computational intelligence ; v. 368
Chapter number 2
Total chapters 14
Start page 15
End page 24
Total pages 10
Publisher Springer
Place of Publication Berlin, Germany
Keyword(s) pattern recognition
handwritten recognition
recognition rate
Summary Offline handwritten recognition is an important automated process in pattern recognition and computer vision field. This paper presents an approach of polar coordinate-based handwritten recognition system involving Support Vector Machines (SVM) classification methodology to achieve high recognition performance. We provide comparison and evaluation for zoning feature extraction methods applied in Polar system. The recognition results we proposed were trained and tested by using SVM with a set of 650 handwritten character images. All the input images are segmented (isolated) handwritten characters. Compared with Cartesian based handwritten recognition system, the recognition rate is more stable and improved up to 86.63%.
ISBN 3642222889
9783642222887
ISSN 1860-949X
Language eng
Field of Research 080109 Pattern Recognition and Data Mining
Socio Economic Objective 970108 Expanding Knowledge in the Information and Computing Sciences
HERDC Research category B1 Book chapter
Copyright notice ©2011, Springer-Verlag Berlin Heidelberg
Persistent URL http://hdl.handle.net/10536/DRO/DU:30043171

Document type: Book Chapter
Collection: School of Information Technology
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