Study on Segmentation Algorithm for Unconstrained Handwritten Numeral Strings

Author

Chuang, Zhang ; Zhiqing, Lin ; Jun, Guo

Author_Institution

Sch. of Telecommun. Eng., Beijing Univ. of Posts & Telecommun.

Volume

2

fYear

2005

Firstpage

1242

Lastpage

1247

Abstract

In this paper, an integrated system of segmenting unconstrained handwritten numeral strings with unknown number of digits is proposed. The algorithm consists of the extraction of connected components based on vertical projection and isolated components analysis, the length estimation of connected components using syntax analysis and waveform analysis and the segmentation of unconstrained connected handwritten numeral strings using innovative reverse "drop-falling" algorithm. This segmentation system which has promising results is then incorporated into a complete bank check character recognition system

Keywords

feature extraction; handwritten character recognition; image segmentation; waveform analysis; bank check character recognition system; connected component extraction; isolated components analysis; length estimation; reverse drop-falling algorithm; segmentation algorithm; syntax analysis; unconstrained handwritten numeral strings; vertical projection; waveform analysis; Algorithm design and analysis; Character recognition; Dispersion; Handwriting recognition; Histograms; Image analysis; Image recognition; Image segmentation; Office automation; Partitioning algorithms;

fLanguage

English

Publisher

ieee

Conference_Titel

Neural Networks and Brain, 2005. ICNN&B '05. International Conference on

Conference_Location

Beijing

Print_ISBN

0-7803-9422-4

Type

conf

DOI

10.1109/ICNNB.2005.1614837

Filename

1614837