HMM Based Handwritten Word Recognition System by Using Singularities

Author

Impedovo, Sebastiano ; Ferrante, Anna ; Modugno, Raffaele

Author_Institution

Dipt. di Inf., Univ. di Bari, Bari, Italy

fYear

2009

Firstpage

783

Lastpage

787

Abstract

This paper presents a new approach for handwritten word recognition based on hidden Markov model theory and the sliding windows technique. The new approach uses specific singularity markers to support the recognition phase: the static marker and the dynamic marker. Moreover, different strategies for sliding windows step are considered: regular step and progressive step. Experimental results showing the improvements obtained for basic word lexicon recognition are reported in the paper.

Keywords

handwritten character recognition; hidden Markov models; image recognition; HMM; dynamic marker; handwritten word recognition system; hidden Markov model theory; progressive step; regular step; singularity marker; sliding window technique; static marker; Character recognition; Computer networks; Handwriting recognition; Hidden Markov models; Histograms; Humans; Impedance; Prototypes; Speech recognition; Text analysis; Basic Words; Hidden Markov Models; Pattern Recognition; Singularities; Sliding Windows;

fLanguage

English

Publisher

ieee

Conference_Titel

Document Analysis and Recognition, 2009. ICDAR '09. 10th International Conference on

Conference_Location

Barcelona

ISSN

1520-5363

Print_ISBN

978-1-4244-4500-4

Electronic_ISBN

1520-5363

Type

conf

DOI

10.1109/ICDAR.2009.73

Filename

5277509