HMM-KNN word recognition engine for bank cheque processing

Author

Guillevic, Didier ; Suen, Ching Y.

Author_Institution

C&C Media Res. Labs., NEC Corp., Kawasaki, Japan

Volume

2

fYear

1998

fDate

16-20 Aug 1998

Firstpage

1526

Abstract

Describes the mixed HMM-KNN word recognition module of a bank cheque processing system developed at CENPARMI. It uses a combination of 2 segmentation free word recognition schemes. The first scheme uses a set of global features associated to a modified K nearest neighbour classifier; while the second one uses a set of directional contour features as input to an HMM. The system has been designed to be modular and independent of specific languages as in Canada one has to deal with at least 2 languages, namely English and French. It can be easily adapted to read other European languages based on the Roman alphabet. The system is continuously tested on data from the local phone company, and we report here the results on a database of approximately 4,500 cheques

Keywords

cheque processing; feature extraction; handwritten character recognition; hidden Markov models; CENPARMI; Canada; English; French; HMM-KNN word recognition engine; Roman alphabet; bank cheque processing; directional contour features; global features; Databases; Engines; Feature extraction; Hidden Markov models; Histograms; Law; Legal factors; National electric code; Natural languages; System testing;

fLanguage

English

Publisher

ieee

Conference_Titel

Pattern Recognition, 1998. Proceedings. Fourteenth International Conference on

Conference_Location

Brisbane, Qld.

ISSN

1051-4651

Print_ISBN

0-8186-8512-3

Type

conf

DOI

10.1109/ICPR.1998.711998

Filename

711998