Vlontzos, J.A.,
Kung, S.Y.,
Hidden Markov Models For Character Recognition,
IP(1), No. 4, October 1992, pp. 539-543.
IEEE DOI
BibRef
9210
Elms, A.J.,
Illingworth, J.,
Combination of HMMs for the Representation of Printed Characters
in Noisy Document Images,
IVC(13), No. 5, June 1995, pp. 385-392.
Elsevier DOI
BibRef
9506
Elms, A.J.,
Illingworth, J., and
Procter, S.,
The Advantage of Using an HMM-based Approach for Faxed Word Recognition,
IJDAR(1), No. 1, Spring 1998, pp. xx-yy.
BibRef
9800
Elms, A.J.[Andrew J.],
The Representation and Recognition of Text
Using Hidden Markov Models,
Ph.D.Thesis, University of Surrey, 1996.
HTML Version.
BibRef
9600
Elms, A.J.,
Procter, S.[Steve],
Illingworth, J.[John],
The recognition of handwritten digit strings of unknown length using
hidden Markov models,
ICPR98(Vol II: 1515-1517).
IEEE DOI
9808
Variable-Depth Level Building for HMM-Based Recognition of
Handwritten Text
BibRef
Elms, A.J.,
Illingworth, J.,
A Hidden Markov Model Approach for Degraded and
Connected Character Recognition: A European Perspective,
IEE Digest(123), No. 8, 1994, pp. 1-7.
BibRef
9400
Elms, A.J.,
A Connected Character Recogniser Using Level Building of HMMS,
ICPR94(B:439-441).
IEEE DOI
BibRef
9400
Elms, A.J.,
Illingworth, J.,
The Recognition of Noise Polyfont Printed Text Using Combined HMMS,
SDAIR95(203-216).
BibRef
9500
Earlier:
Modelling Polyfont Printed Characters with HMMS and a
Shift Invariant Hamming Distance,
ICDAR95(504-507).
BibRef
Earlier:
Combination HMMs for the Recognition of Noisy Printed Characters,
BMVC94(185-194).
PDF File.
9409
BibRef
Kim, H.J.[Hang Joon],
Kim, S.K.[Sang Kyoon],
Kim, K.H.[Kyung Hyun],
Lee, J.K.[Jong Kook],
An HMM-Based Character-Recognition Network Using Level Building,
PR(30), No. 3, March 1997, pp. 491-502.
Elsevier DOI
9705
BibRef
Schenkel, M.,
Jabri, M.,
Low-Resolution, Degraded Document Recognition Using
Neural Networks and Hidden Markov Models,
PRL(19), No. 3-4, March 1998, pp. 365-371.
9807
BibRef
Yen, C.,
Kuo, S.,
Lee, C.H.,
Minimum Error Rate Training for PHMM-Based Text Recognition,
IP(8), No. 8, August 1999, pp. 1120-1124.
IEEE DOI
BibRef
9908
Zimmermann, M.,
Bunke, H.,
Hidden markov model length optimization for handwriting recognition
systems,
FHR02(369-374).
IEEE Top Reference.
0209
BibRef
Earlier:
Automatic segmentation of the IAM off-line database for handwritten
English text,
ICPR02(IV: 35-39).
IEEE DOI
0211
BibRef
Anigbogu, J.C.,
Belaid, A.,
Performance evaluation of an HMM based OCR system,
ICPR92(II:565-568).
IEEE DOI
9208
BibRef
Ma, Y.L.,
Pattern Recognition by Markovian Dynamic Programming,
ICPR84(1259-1262).
BibRef
8400
Chapter on OCR, Document Analysis and Character Recognition Systems continues in
Character Segmentation, Segmentation of Individual Characters .