Fusion of Segmentation Strategies for Off-Line Cursive Handwriting Recognition

Fusion of Segmentation Strategies for Off-Line Cursive Handwriting Recognition

Brijesh Verma (Central Queensland University, Australia) and Michael Blumenstein (Griffith University, Australia)
Copyright: © 2008 |Pages: 16
DOI: 10.4018/978-1-59904-807-9.ch001
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Abstract

Cursive handwriting recognition is a challenging task for many real-world applications such as document authentication, form processing, postal address recognition, reading machines for the blind, bank check recognition, and interpretation of historical documents. Therefore, in the last few decades, researchers have put an enormous effort into developing various techniques for handwriting recognition. This chapter reviews existing handwriting recognition techniques and presents the current state of the art in cursive handwriting recognition. The chapter also presents segmentation strategies and a segmentation- based approach for automated recognition of unconstrained cursive handwriting. The chapter provides a comprehensive literature review with basic and advanced techniques and research results in handwriting recognition for graduate students as well as for advanced researchers.

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