Polar Transformation System for Offline Handwritten Character Recognition

  • Xianjing Wang
  • Atul Sajjanhar
Conference paper
Part of the Studies in Computational Intelligence book series (SCI, volume 368)

Abstract

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%.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Xianjing Wang
    • 1
  • Atul Sajjanhar
    • 1
  1. 1.School of Information TechnologyDeakin UniversityBurwoodAustralia

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