25.4.6.3 Handwriting, Cursive Script Recognition Systems

Chapter Contents (Back)
Recognize Handwriting. Cursive Character Recognition. Recognize Cursive Script. Offline. For online:
See also On-Line Cursive Script Recognition Systems.

Eden, M.,
Handwriting and pattern Recognition,
IT(8), 1962, pp. 160-166. BibRef 6200

Ehrich, R.W., and Koehler, K.J.,
Experiments in the Contextual Recognition of Cursive Script,
TC(24), No. 2, February 1975, pp. 182-194. BibRef 7502

Peleg, S.[Shmuel],
Ambiguity Reduction in Handwriting with Ambiguous Segmentation and Uncertain Interpretation,
CGIP(10), No. 3, July 1979, pp. 235-245.
Elsevier DOI BibRef 7907

Duvernoy, J., Charraut, D.,
Stability and stationarity of cursive handwriting,
PR(11), No. 3, 1979, pp. 145-154.
Elsevier DOI 0309
BibRef

Myers, C.S., Rabiner, L.R., Rosenberg, A.E.,
Performance, Tradeoffs in Dynamic Time Warping Algorithms for Isolated Word Recognition,
ASSP(28), No. 6, December 1980, pp. 623-635. BibRef 8012

Myers, C.S., Rabiner, L.R.,
A Level Building Dynamic Time Warping Algorithm for Connected Word Recognition,
ASSP(29), No. 2, 1981, pp. 284-297. BibRef 8100

Lee, C., Rabiner, L.R.,
A Frame-Synchronous Network Search Algorithm for Connected Word Recognition,
ASSP(37), No. 11, November 1989, pp. 1649-1658. BibRef 8911

Burr, D.J.,
Designing a Handwriting Reader,
PAMI(5), No. 5, September 1983, pp. 554-559. BibRef 8309

Babcock, M.K., and Freyd, J.J.,
Perception of Dynamic Information in Static Handwritten Forms,
Am. J. Psychology(101), No. 1, 1988, pp.111-130. BibRef 8800

Mermelstein, P., and Eden, M.,
Experiments of Computer Recognition of Connected Handwritten Words,
InfoControl(7), No. 2, 1964, pp. 255-270. BibRef 6400

Tappert, C.C.,
Cursive Script by Elastic matching,
IBMRD(26), No. 6, November 1982, pp. 765-771. Restrict to n-grams, sequences of characters. BibRef 8211

Edelman, S., Ullman, S., and Flash, T.,
Reading Cursive Handwriting by Alignment of Letter Prototypes,
IJCV(5), No. 3, December 1990, pp. 303-331.
Springer DOI Recognize Cursive Script. BibRef 9012

Bozinovic, R.M.[Radmilo M.], Srihari, S.N.[Sargur N.],
A String Correction Algorithm for Cursive Script Recognition,
PAMI(4), No. 6, November 1982, pp. 655-663. BibRef 8211

Srihari, S.N.[Sargur N.], and Bozinovic, R.M.[Radmilo M.],
A Multi-Level Perception Approach to Reading Cursive Script,
AI(33), No. 2, October 1987, pp. 217-255.
Elsevier DOI BibRef 8710
Earlier: IJCAI87(844-847). Recognize Cursive Script. BibRef

Bozinovic, R.M.[Radmilo M.], Srihari, S.N.[Sargur N.],
Off-Line Cursive Script Word Recognition,
PAMI(11), No. 1, January 1989, pp. 68-83.
IEEE DOI BibRef 8901
Earlier:
Knowledge-Based Cursive Script Interpretation,
ICPR84(774-776). BibRef

Morasso, P., Barberis, L., Pagliano, S., and Vergano, D.,
Recognition Experiments of Cursive Dynamic Handwriting with Self-Organizing Networks,
PR(26), No. 3, March 1993, pp. 451-460.
Elsevier DOI BibRef 9303

Boccignone, G., Chianese, A., Cordella, L.P., Marcelli, A.,
Recovering dynamic information from static handwriting,
PR(26), No. 3, March 1993, pp. 409-418.
Elsevier DOI 0401
BibRef

Chianese, A., de Santo, M., Picariello, A.,
Improving the use of contours and skeletons for off-line cursive script segmentation,
CIAP97(II: 600-607).
Springer DOI 9709
BibRef

Boccignone, G., de Santo, M., Chianese, A., Picariello, A.,
Improving the use of contours for off-line Cursive Script Segmentation,
CIAP95(545-550).
Springer DOI 9509
BibRef

Seni, G.[Giovanni], Cohen, E.[Edward],
External Word Segmentation of Off-Line Handwritten Text Lines,
PR(27), No. 1, January 1994, pp. 41-52.
Elsevier DOI Line into words. BibRef 9401

Gorsky, N.D.,
Experiments with Handwriting Recognition Using Holographic Representation of Line Images,
PRL(15), No. 9, September 1994, pp. 853-859. BibRef 9409

Setlur, S., Govindaraju, V.,
Generating Manifold Samples from a Handwritten Word,
PRL(15), No. 9, September 1994, pp. 901-905. BibRef 9409

Cheriet, M., Suen, C.Y.,
Extraction of Key Letters for Cursive Script Recognition,
PRL(14), No. 12, December 1993, pp. 1009-1017. BibRef 9312

Abdelazim, H.Y.[Hazem Y.],
Recognition of characters in cursive script,
US_Patent5,335,289, August 2, 1994.
WWW Link. BibRef 9408

Doermann, D.S., and Rosenfeld, A.,
Recovery of Temporal Information from Static Images of Handwriting,
IJCV(15), No. 1-2, June 1995, pp. 143-164.
Springer DOI BibRef 9506
Earlier: CVPR92(162-168).
IEEE DOI BibRef
And:
The Interpretation and Reconstruction of Interfering Strokes,
FHR93(41-50). BibRef
Earlier:
Temporal clues in handwriting,
ICPR92(II:317-320).
IEEE DOI 9208
Trace the strokes. BibRef

Nishida, H.[Hirobumi],
Model-Based Shape-Matching with Structural Feature Grouping,
PAMI(17), No. 3, March 1995, pp. 315-320.
IEEE DOI BibRef 9503
Earlier: ICPR94(B:599-601).
IEEE DOI 9410
Handwritten numbers and letters. BibRef

Nishida, H.[Hirobumi],
Character recognition method,
US_Patent5,067,165, Nov 19, 1991
WWW Link. BibRef 9111

Nishida, H.[Hirobumi],
Method for extracting features from on-line handwritten characters,
US_Patent5,313,528, May 17, 1994.
WWW Link. BibRef 9405

Nishida, H.[Hirobumi],
Shape-recognition by Integrating Structural Descriptions and Geometrical/Statistical Transforms,
CVIU(64), No. 2, September 1996, pp. 248-262.
DOI Link BibRef 9609

Nishida, H.[Hirobumi],
Structural Shape Indexing with Feature Generation Models,
CVIU(73), No. 1, January 1999, pp. 121-136.
DOI Link BibRef 9901

Nishida, H.[Hirobumi],
Robust Structural Indexing through Quasi-Invariant Shape Signatures and Feature Generation,
VF01(696 ff.).
Springer DOI 0209
BibRef

Rose, T.G., Evett, L.J.,
The Use of Context in Cursive Script Recognition,
MVA(8), No. 4, 1995, pp. 241-248.
Springer DOI BibRef 9500

Bramall, P.E., Higgins, C.A.,
A Cursive Script-Recognition System Based on Human Reading Models,
MVA(8), No. 4, 1995, pp. 224-231.
Springer DOI BibRef 9500

Wunsch, P.[Patrick], Laine, A.F.[Andrew F.],
Wavelet Descriptors for Multiresolution Recognition of Handprinted Characters,
PR(28), No. 8, August 1995, pp. 1237-1249.
Elsevier DOI Shape descriptors. BibRef 9508

Oh, S.C., Ha, J.Y., Kim, J.H.,
Context-Dependent Search in Interconnected Hidden Markov Model for Unconstrained Handwriting Recognition,
PR(28), No. 11, November 1995, pp. 1693-1704.
Elsevier DOI BibRef 9511

Rao, P.V.S.,
A Knowledge-Based Approach for Script Recognition Without Training,
PAMI(17), No. 12, December 1995, pp. 1233-1239.
IEEE DOI 90% recognition of hand written script. BibRef 9512

Keller, J.M., Gader, P.D., Tahani, H., Chiang, J.H., Mohamed, M.A.,
Advances in Fuzzy Integration for Pattern Recognition,
PRL(15), 1994, pp. 273-283. BibRef 9400

Gader, P.D., Keller, J.M., Krishnapuram, R., Chiang, J.H., Mohamed, M.A.,
Neural and Fuzzy Methods in Handwriting Recognition,
Computer(30), No. 2, February 1997, pp. 79-86. 9702
BibRef

Lim, J.H., Teh, H.H., Lui, H.C., Wang, P.Z.,
Stochastic Topology with Elastic Matching for Off-Line Handwritten Character-Recognition,
PRL(17), No. 2, February 8 1996, pp. 149-154. 9603
BibRef
And: Correction: PRL(17), No. 7, June 10 1996, pp. 801-801. 9607
BibRef

Seni, G., Kripasundar, V., Srihari, R.K.,
Generalizing Edit Distance to Incorporate Domain Information: Handwritten Text Recognition as a Case-Study,
PR(29), No. 3, March 1996, pp. 405-414.
Elsevier DOI BibRef 9603

Nishida, H.,
Automatic Construction of Structural Models Incorporating Discontinuous Transformations,
PAMI(18), No. 4, April 1996, pp. 400-411.
IEEE DOI 9605
For general application of the model:
See also Structural Model of Curve Deformation by Discontinuous Transformations, A. BibRef

Bouchaffra, D., Koontz, E., Krpasundar, V., Srihari, R.K.,
Incorporating Diverse Information-Sources in Handwriting Recognition Postprocessing,
IJIST(7), No. 4, Winter 1996, pp. 320-329. 9612
BibRef

Hochberg, J.[Judith], Kelly, P.[Patrick], Thomas, T.[Timothy], Kerns, L.[Lila],
Automatic Script Identification from Document Images Using Cluster-Based Templates,
PAMI(19), No. 2, February 1997, pp. 176-181.
IEEE DOI 9703
BibRef
Earlier: A1, A4, A3 only:
Automatic Script Identification from Images Using Cluster-Based Templates,
ICDAR95(378-381). Determine what kind of script is being used based on a demplate of the different scripts. Applied to Arabic, Armenian, Burmese, Chinese, Cyrillic, Devanagari, Ethopic, Greek, Hebrew, Japanese, Korean, Roman, Thai scripts. BibRef

Hochberg, J.[Judith], Bowers, K.[Kevin], Cannon, M.[Michael], Kelly, P.[Patrick],
Script and Language Identification for Handwritten Document Images,
IJDAR(2), No. 2/3, 1999, pp. 45-52. 9912
BibRef

Malaviya, A.[Ashutosh], Peters, L.[Liliane],
Fuzzy Feature Description of Handwriting Patterns,
PR(30), No. 10, October 1997, pp. 1591-1604.
Elsevier DOI 9712
BibRef

Malaviya, A.[Ashutosh], Peters, L.[Liliane],
Fuzzy handwriting description language: FOHDEL,
PR(33), No. 1, January 2000, pp. 119-131.
Elsevier DOI 0005
BibRef

Errico, J.H.[James H.], Labun, N.M.[Nicholas M.], Murdock, M.C.[Michael C.], Wang, S.P.T.[Shay-Ping T.],
Method and system using meta-classes and polynomial discriminant functions for handwriting recognition,
US_Patent5,854,855, December 29, 1998.
WWW Link. BibRef 9812

Murdock, M.C.[Michael C.], Wang, S.P.T.[Shay-Ping T.],
Method and system for recognizing a boundary between characters in handwritten text,
US_Patent5,818,963, Oct 6, 1998
WWW Link. BibRef 9810

Senior, A.W.[Andrew W.], Robinson, A.J.[Anthony J.],
An Off-Line Cursive Handwriting Recognition System,
PAMI(20), No. 3, March 1998, pp. 309-321.
IEEE DOI 9805
Segmentation. Normailze for scale, slant, stroke thickness. Represent as skeleton and stroke features. Use a Neural Network. Use a lexicon BibRef

Senior, A.W.[Andrew W.], Fallside, F.,
Off-line Handwriting Recognition by Recurrent Error Propagation Networks,
BMVC92(xx-yy).
PDF File. 9209
BibRef

AbuHaiba, I.S.I., Holt, M.J.J., Datta, S.,
Recognition of Off-Line Cursive Handwriting,
CVIU(71), No. 1, July 1998, pp. 19-38.
DOI Link BibRef 9807

Plamondon, R., Privitera, C.M.,
The Segmentation of Cursive Handwriting: An Approach Based on Off-Line Recovery of the Motor-Temporal Information,
IP(8), No. 1, January 1999, pp. 80-91.
IEEE DOI BibRef 9901

Liou, C.Y., Yang, H.C.,
Selective Feature-to-Feature Adhesion for Recognition of Cursive Handprinted Characters,
PAMI(21), No. 2, February 1999, pp. 184-191. 748829 BibRef 9902

Wang, J.G.[Jian-Guo], Yan, H.[Hong],
Mending broken handwriting with a macrostructure analysis method to improve recognition,
PRL(20), No. 8, August 1999, pp. 855-864.
See also hybrid method for unconstrained handwritten numeral recognition by combining structural and neural gas classifiers, A. BibRef 9908

Schomaker, L.R.B.[Lambert R.B.], Segers, E.[Eliane],
Finding features used in the human reading of cursive handwriting,
IJDAR(2), No. 1, 1999, pp. 13-18. BibRef 9900

Seni, G.[Giovanni], Seybold, J.[John],
Diacritical processing for unconstrained online handwriting recognition using a forward search,
IJDAR(2), No. 1, 1999, pp. 24-29. BibRef 9900

Kim, G.H.[Gyeong-Hwan], Govindaraju, V.[Venu], Srihari, S.N.[Sargur N.],
An architecture for handwritten text recognition systems,
IJDAR(2), No. 1, 1999, pp. 37-44. BibRef 9900

Wang, X.[Xian], Govindaraju, V.[Venu], Srihari, S.N.[Sargur N.],
Holistic recognition of handwritten character pairs,
PR(33), No. 12, December 2000, pp. 1967-1973.
Elsevier DOI 0008
BibRef

Steinherz, T.[Tal], Rivlin, E.[Ehud], Intrator, N.[Nathan],
Offline Cursive Script Word Recognition: A Survey,
IJDAR(2), No. 2/3, 1999, pp. 90-110. 9912
Survey, Handwriting. BibRef

Steinherz, T.[Tal], Doermann, D.S.[David S.], Rivlin, E.[Ehud], Intrator, N.[Nathan],
Offline Loop Investigation for Handwriting Analysis,
PAMI(31), No. 2, February 2009, pp. 193-209.
IEEE DOI 0901
Analysis of loops in handwriting. BibRef

Procter, S., Illingworth, J., Mokhtarian, F.,
Cursive handwriting recognition using hidden Markov models and a lexicon-driven level building algorithm,
VISP(147), No. 4, 2000, pp. 332-339. 0010
BibRef

Procter, S., Illingworth, J.,
Combining HMM classifiers in a handwritten text recognition system,
ICIP98(II: 934-938).
IEEE DOI 9810
BibRef

Kato, Y.[Yoshiharu], Yasuhara, M.[Makoto],
Recovery of Drawing Order from Single-Stroke Handwriting Images,
PAMI(22), No. 9, September 2000, pp. 938-949.
IEEE DOI 0010
BibRef
And:
Recovery of Drawing Order from Scanned Images of Multi-Stroke Handwriting,
ICDAR99(261-264).
IEEE DOI From static image, trace the order of the script. BibRef

Qiao, Y.[Yu], Nishiara, M., Yasuhara, M.[Makoto],
A Framework Toward Restoration of Writing Order from Single-Stroked Handwriting Image,
PAMI(28), No. 11, November 2006, pp. 1724-1737.
IEEE DOI 0609
BibRef
Earlier:
A novel approach to recover writing order from single stroke offline handwritten images,
ICDAR05(I: 227-231).
IEEE DOI 0508
Approach as finding smoothest path in a graph. BibRef

Huang, T., and Yasuhara, M.[Makoto],
A Total Stroke SLALOM Method for Searching for the Optimal Drawing Order of Off-Line Handwriting,
SMC-C95(2789-2794). BibRef 9500

Hennig, A., Sherkat, N.,
Cursive Script Recognition using Wildcards and Multiple Experts,
PAA(4), No. 1, 2001, pp. 51-60.
Springer DOI 0105
BibRef

Hennig, A., Sherkat, N.,
Exploiting zoning based on approximating splines in cursive script recognition,
PR(35), No. 2, February 2002, pp. 445-454.
Elsevier DOI 0201
BibRef

Arica, N.[Nafiz], Yarman-Vural, F.T.[Fatos T.],
One-dimensional representation of two-dimensional information for HMM based handwriting recognition,
PRL(21), No. 6-7, June 2000, pp. 583-592. 0006
BibRef
Earlier: ICIP98(II: 948-952).
IEEE DOI 9810
BibRef

Arica, N.[Nafiz], Yarman-Vural, F.T.[Fatos T.],
Optical Character Recognition for Cursive Handwriting,
PAMI(24), No. 6, June 2002, pp. 801-813.
IEEE DOI 0206
Estimate some global parameters (slant, etc.). Segment character paths. Apply HMM for shape recognition on characters. Lexicon and character rank to find optimal recognition. BibRef

Kavallieratou, E., Fakotakis, N., Kokkinakis, G.,
An unconstrained handwriting recognition system,
IJDAR(4), No. 4, 2002, pp. 226-242.
Springer DOI 0208
BibRef
And:
Handwritten character recognition based on structural characteristics,
ICPR02(III: 139-142).
IEEE DOI 0211
BibRef

Kavallieratou, E., Sgarbas, K., Fakotakis, N., Kokkinakis, G.,
Handwritten word recognition based on structural characteristics and Lexical support,
ICDAR03(562-566).
IEEE DOI 0311
BibRef

Liolios, N., Kavallieratou, E., Fakotakis, N., Kokkinakis, G.,
A new shape transformation approach to handwritten character recognition,
ICPR02(I: 584-587).
IEEE DOI 0211
BibRef

Dehkordi, M.E.[Mandana Ebadian], Sherkat, N.[Nasser], Allen, T.[Tony],
Handwriting style classification,
IJDAR(6), No. 1, 2003, pp. 55-74.
Springer DOI 0308
BibRef
Earlier:
Prediction of handwriting legibility,
ICDAR01(997-1001).
IEEE DOI 0109
BibRef

Chi, Z.[Zheru], Wang, Q.[Qing], Siu, W.C.[Wan-Chi],
Hierarchical content classification and script determination for automatic document image processing,
PR(36), No. 11, November 2003, pp. 2483-2500.
Elsevier DOI 0309
BibRef
Earlier: A2, A1, Different A3: Zhao, R.[Rongehun], ICPR02(III: 77-80).
IEEE DOI 0211
BibRef

Günter, S.[Simon], Bunke, H.[Horst],
Optimization of Weights in a Multiple Classifier Handwritten Word Recognition System Using a Genetic Algorithm,
ELCVIA(3), No. 1, 2004, pp. 25-44.
DOI Link 0402
BibRef
Earlier:
Fast Feature Selection in an HMM-Based Multiple Classifier System for Handwriting Recognition,
DAGM03(289-296).
Springer DOI 0310
BibRef

Günter, S.[Simon], Bunke, H.[Horst],
Ensembles of classifiers for handwritten word recognition,
IJDAR(5), No. 4, July 2003, pp. 224-232.
Springer DOI 0308
Word Recognition. BibRef
Earlier:
A new combination scheme for HMM-based classifiers and its application to handwriting recognition,
ICPR02(II: 332-337).
IEEE DOI 0211
BibRef
And:
Creation of classifier ensembles for handwritten word recognition using feature selection algorithms,
FHR02(183-188).
IEEE Top Reference. 0209
BibRef

Gunter, S., Bunke, H.,
An evaluation of ensemble methods in handwritten word recognition based on feature selection,
ICPR04(I: 388-392).
IEEE DOI 0409
BibRef

Zheng, Y.F.[Ye-Feng], Li, H.P.[Hui-Ping], Doermann, D.S.[David S.],
Machine printed text and handwriting identification in noisy document images,
PAMI(26), No. 3, March 2004, pp. 337-353.
IEEE Abstract. 0402
BibRef
Earlier:
Text identification in noisy document images using Markov random field,
ICDAR03(599-603).
IEEE DOI 0311
BibRef
Earlier:
The Segmentation and Identification of Handwriting in Noisy Document Images,
DAS02(95 ff.).
Springer DOI 0303
BibRef

Wolf, C., Doermann, D.S.,
Binarization of low quality text using a Markov random field model,
ICPR02(III: 160-163).
IEEE DOI 0211
BibRef

Zheng, Y.F.[Ye-Feng], Doermann, D.S.,
Handwriting matching and its application to handwriting synthesis,
ICDAR05(II: 861-865).
IEEE DOI 0508
BibRef

Veeramachaneni, S.[Sriharsha], Nagy, G.[George],
Style Context with Second-Order Statistics,
PAMI(27), No. 1, January 2005, pp. 14-22.
IEEE Abstract. 0412
BibRef
Earlier:
Towards a Ptolemaic Model for OCR,
ICDAR03(1060-1064).
IEEE DOI 0311
Style Context: dependencies between patterns. Reduce error rate on digits. BibRef

Veeramachaneni, S.[Sriharsha], Nagy, G.[George],
Analytical Results on Style-Constrained Bayesian Classification of Pattern Fields,
PAMI(29), No. 7, July 2007, pp. 1280-1285.
IEEE DOI 0706
Style context is the basis for order independent field classification.
See also Style Consistent Classification of Isogenous Patterns. BibRef

El-Nasan, A., Veeramachaneni, S., Nagy, G.,
Handwriting recognition using position sensitive letter N-gram matching,
ICDAR03(577-582).
IEEE DOI 0311
BibRef
Earlier:
Word discrimination based on bigram co-occurrences,
ICDAR01(149-153).
IEEE DOI 0109
BibRef

El-Nasan, A., Perrone, M.P.,
On-line handwriting recognition using character bigram match vectors,
FHR02(67-71).
IEEE Top Reference. 0209
BibRef

El-Nasan, A., Nagy, G.,
On-line handwriting recognition based on bigram co-occurrences,
ICPR02(III: 740-743).
IEEE DOI 0211
BibRef

Veeramachaneni, S.[Sriharsha],
Style Constrained Quadratic Field Classifiers,
Ph.D.Thesis, RPI, Troy, NY, 2002. BibRef 0200

Vincent, N., Seropian, A., Stamon, G.,
Synthesis for handwriting analysis,
PRL(26), No. 3, February 2005, pp. 267-275.
Elsevier DOI 0501
BibRef

Steinherz, T.[Tal], Rivlin, E.[Ehud], Intrator, N.[Nathan], Neskovic, P.[Predrag],
An Integration of Online and Pseudo-Online Information for Cursive Word Recognition,
PAMI(27), No. 5, May 2005, pp. 669-683.
IEEE Abstract. 0501
Use stroke order information and an offline style recognition. Word level recognition. BibRef

Doermann, D.S., Intrator, N., Rivlin, E., Steinherz, T.,
Hidden loop recovery for handwriting recognition,
FHR02(375-380).
IEEE Top Reference. 0209
BibRef

Wang, J.[Jue], Wu, C.Y.[Chen-Yu], Xu, Y.Q.[Ying-Qing], Shum, H.Y.[Heung-Yeung],
Combining shape and physical models for online cursive handwriting synthesis,
IJDAR(7), No. 4, September 2005, pp. 219-227.
Springer DOI 0512
BibRef

Wang, J.[Jue], Wu, C.Y.[Chen-Yu], Xu, Y.Q.[Ying-Qing], Shum, H.Y.[Heung-Yeung], Ji, L.[Liang],
Learning-based cursive handwriting synthesis,
FHR02(157-162).
IEEE Top Reference. 0209
BibRef

Viard-Gaudin, C.[Christian], Lallican, P.M.[Pierre-Michel], Knerr, S.[Stefan],
Recognition-directed recovering of temporal information from handwriting images,
PRL(26), No. 16, December 2005, pp. 2537-2548.
Elsevier DOI 0512
BibRef

Fujioka, H., Kano, H., Nakata, H., Shinoda, H.,
Constructing and Reconstructing Characters, Words, and Sentences by Synthesizing Writing Motions,
SMC-A(36), No. 4, July 2006, pp. 661-670.
IEEE DOI 0606
BibRef

Lin, Z.C.[Zhou-Chen], Wan, L.[Liang],
Style-preserving English handwriting synthesis,
PR(40), No. 7, July 2007, pp. 2097-2109.
Elsevier DOI 0704
Handwriting; Handwriting synthesis; Writing style; Cursive; Connection BibRef

Adankon, M.M.[Mathias M.], Cheriet, M.[Mohamed],
Model selection for the LS-SVM. Application to handwriting recognition,
PR(42), No. 12, December 2009, pp. 3264-3270.
Elsevier DOI 0909
LS-SVM; Support vector machine; Model selection; Kernel machine BibRef

Vikram, T.N., Gowda, K.C.[K. Chidananda],
Subspace models for document script and language identification,
IJIST(20), No. 2, June 2010, pp. 140-148.
DOI Link 1006
BibRef

Vikram, T.N., Guru, D.S.,
Appearance Based Models in Document Script Identification,
ICDAR07(709-713).
IEEE DOI 0709
BibRef

Plötz, T.[Thomas], Fink, G.A.[Gernot A.],
Markov Models for Handwriting Recognition,
Springer2011. ISBN: 978-1-4471-2187-9.
WWW Link. 1109
BibRef

Quiniou, S.[Solen], Cheriet, M.[Mohamed], Anquetil, E.[Eric],
Error handling approach using characterization and correction steps for handwritten document analysis,
IJDAR(15), No. 2, June 2012, pp. 125-141.
WWW Link. 1205
BibRef

Romero, V.[Verónica], Fornés, A.[Alicia], Serrano, N.[Nicolás], Sánchez, J.A.[Joan Andreu], Toselli, A.H.[Alejandro H.], Frinken, V.[Volkmar], Vidal, E.[Enrique], Lladós, J.[Josep],
The ESPOSALLES database: An ancient marriage license corpus for off-line handwriting recognition,
PR(46), No. 6, June 2013, pp. 1658-1669.
Elsevier DOI 1302
BibRef
Earlier: A1, A4, A3, A7, Only:
Handwritten Text Recognition for Marriage Register Books,
ICDAR11(533-537).
IEEE DOI 1111
Handwritten text recognition; Marriage register books; Hidden Markov models; BLSTM; Neural networks BibRef

Serrano, N.[Nicolás], Civera, J., Sanchis, A., Juan, A.[Alfons],
Effective balancing error and user effort in interactive handwriting recognition,
PRL(37), No. 1, 2014, pp. 135-142.
Elsevier DOI 1402
Handwriting recognition BibRef

Serrano, N.[Nicolás], Gimenez, A.[Adriŕ], Civera, J.[Jorge], Sanchis, A.[Alberto], Juan, A.[Alfons],
Interactive handwriting recognition with limited user effort,
IJDAR(17), No. 1, March 2014, pp. 47-59.
Springer DOI 1403
BibRef

Martín-Albo, D.[Daniel], Romero, V.[Verónica], Vidal, E.[Enrique],
An Experimental Study of Pruning Techniques in Handwritten Text Recognition Systems,
IbPRIA13(559-566).
Springer DOI 1307
BibRef

Frinken, V.[Volkmar], Fischer, A.[Andreas], Baumgartner, M.[Markus], Bunke, H.[Horst],
Keyword spotting for self-training of BLSTM NN based handwriting recognition systems,
PR(47), No. 3, 2014, pp. 1073-1082.
Elsevier DOI 1312
Document retrieval BibRef

Frinken, V.[Volkmar], Zamora-Martinez, F.[Francisco], Espana-Boquera, S.[Salvador], Castro-Bleda, M.J.[Maria Jose], Fischer, A.[Andreas], Bunke, H.[Horst],
Long-short term memory neural networks language modeling for handwriting recognition,
ICPR12(701-704).
WWW Link. 1302
BibRef

Plamondon, R.[Réjean], O'Reilly, C.[Christian], Galbally, J.[Javier], Almaksour, A.[Abdullah], Anquetil, É.[Éric],
Recent developments in the study of rapid human movements with the kinematic theory: Applications to handwriting and signature synthesis,
PRL(35), No. 1, 2014, pp. 225-235.
Elsevier DOI 1312
Kinematic theory BibRef

Fischer, A., Plamondon, R.[Réjean],
Signature Verification Based on the Kinematic Theory of Rapid Human Movements,
HMS(47), No. 2, April 2017, pp. 169-180.
IEEE DOI 1704
Authentication BibRef

Zamora-Martínez, F., Frinken, V.[Volkmar], Espańa-Boquera, S., Castro-Bleda, M.J., Fischer, A.[Andreas], Bunke, H.[Horst],
Neural network language models for off-line handwriting recognition,
PR(47), No. 4, 2014, pp. 1642-1652.
Elsevier DOI 1402
Handwritten text recognition (HTR) BibRef

Frinken, V.[Volkmar], Peter, T.[Tim], Fischer, A.[Andreas], Bunke, H.[Horst], Do, T.M.T.[Trinh-Minh-Tri], Artieres, T.[Thierry],
Improved Handwriting Recognition by Combining Two Forms of Hidden Markov Models and a Recurrent Neural Network,
CAIP09(189-196).
Springer DOI 0909
BibRef

Cirera, N.[Núria], Fornés, A.[Alícia], Frinken, V.[Volkmar], Lladós, J.[Josep],
Hybrid Grammar Language Model for Handwritten Historical Documents Recognition,
IbPRIA13(117-124).
Springer DOI 1307
BibRef

Frinken, V.[Volkmar], Fornés, A.[Alicia], Lladós, J.[Josep], Ogier, J.M.[Jean-Marc],
Bidirectional Language Model for Handwriting Recognition,
SSSPR12(611-619).
Springer DOI 1211
BibRef

Samanta, O.[Oendrila], Bhattacharya, U.[Ujjwal], Parui, S.K.[Swapan K.],
Smoothing of HMM parameters for efficient recognition of online handwriting,
PR(47), No. 11, 2014, pp. 3614-3629.
Elsevier DOI 1407
Handwriting recognition BibRef

Samanta, O.[Oendrila], Roy, A.[Anandarup], Bhattacharya, U.[Ujjwal], Parui, S.K.[Swapan K.],
Script independent online handwriting recognition,
ICDAR15(1251-1255)
IEEE DOI 1511
BibRef

Elarian, Y.[Yousef], Abdel-Aal, R.[Radwan], Ahmad, I.[Irfan], Parvez, M.T.[Mohammad Tanvir], Zidouri, A.[Abdelmalek],
Handwriting synthesis: classifications and techniques,
IJDAR(17), No. 4, December 2014, pp. 455-469.
Springer DOI 1411
Synthesis based. BibRef

Gottfried, B.[Björn], Wegner, M.[Marius], Lawo, M.[Mathias],
Towards the interactive transcription of handwritings: Anytime anywhere document analysis,
IJDAR(18), No. 1, March 2015, pp. 31-45.
WWW Link. 1503
BibRef

Siegmund, D.[Dirk], Ebert, T.[Tina], Damer, N.[Naser],
Combining Low-Level Features of Offline Questionnaires for Handwriting Identification,
ICIAR16(46-54).
Springer DOI 1608
BibRef

Chherawala, Y.[Youssouf], Roy, P.P.[Partha Pratim], Cheriet, M.[Mohamed],
Combination of context-dependent bidirectional long short-term memory classifiers for robust offline handwriting recognition,
PRL(90), No. 1, 2017, pp. 58-64.
Elsevier DOI 1704
BibRef
Earlier:
Context-dependent blstm models. Application to offline handwriting recognition,
ICIP14(2565-2569)
IEEE DOI 1502
Handwriting recognition Context BibRef

Keysers, D.[Daniel], Deselaers, T.[Thomas], Rowley, H.A.[Henry A.], Wang, L.L.[Li-Lun], Carbune, V.[Victor],
Multi-Language Online Handwriting Recognition,
PAMI(39), No. 6, June 2017, pp. 1180-1194.
IEEE DOI 1705
Character recognition, Google, Handwriting recognition, Hidden Markov models, Ink, Training, Writing, Online handwriting recognition, handwriting, recognition BibRef

Carbune, V.[Victor], Gonnet, P.[Pedro], Deselaers, T.[Thomas], Rowley, H.A.[Henry A.], Daryin, A.[Alexander], Calvo, M.[Marcos], Wang, L.L.[Li-Lun], Keysers, D.[Daniel], Feuz, S.[Sandro], Gervais, P.[Philippe],
Fast multi-language LSTM-based online handwriting recognition,
IJDAR(23), No. 2, June 2020, pp. 89-102.
Springer DOI 2005
BibRef

Bhattacharya, U.[Ujjwal], Plamondon, R.[Réjean], Chowdhury, S.D.[Souvik Dutta], Goyal, P.[Pankaj], Parui, S.K.[Swapan K.],
A sigma-lognormal model-based approach to generating large synthetic online handwriting sample databases,
IJDAR(20), No. 3, September 2017, pp. 155-171.
Springer DOI 1708
BibRef

Bouadjenek, N.[Nesrine], Nemmour, H.[Hassiba], Chibani, Y.[Youcef],
Fuzzy integrals for combining multiple SVM and histogram features for writer's gender prediction,
IET-Bio(6), No. 6, November 2017, pp. 429-437.
DOI Link 1711
BibRef
Earlier:
Age, gender and handedness prediction from handwriting using gradient features,
ICDAR15(1116-1120)
IEEE DOI 1511
Age; GLBP; HOG; gender; handedness; handwriting recognition BibRef

Yan, R.J.[Rui-Jie], Peng, L.R.[Liang-Rui], Xiao, S.[Shanyu], Johnson, M.T.[Michael T.], Wang, S.J.[Sheng-Jin],
Dynamic temporal residual network for sequence modeling,
IJDAR(22), No. 3, September 2019, pp. 235-246.
Springer DOI 1909
Long short-term memory (LSTM). BibRef

Rehman, A.[Amjad], Harouni, M.[Majid], Saba, T.[Tanzila],
Cursive multilingual characters recognition based on hard geometric features,
IJCVR(10), No. 3, 2020, pp. 213-222.
DOI Link 2005
BibRef

Qian, Z.[Zhuang], Huang, K.[Kaizhu], Wang, Q.F.[Qiu-Feng], Xiao, J.[Jimin], Zhang, R.[Rui],
Generative adversarial classifier for handwriting characters super-resolution,
PR(107), 2020, pp. 107453.
Elsevier DOI 2008
Super-Resolution, Generative adversarial networks (GAN), Handwriting characters recognition BibRef

Chen, Z.[Zhuo], Yin, F.[Fei], Zhang, X.Y.[Xu-Yao], Yang, Q.[Qing], Liu, C.L.[Cheng-Lin],
MuLTReNets: Multilingual text recognition networks for simultaneous script identification and handwriting recognition,
PR(108), 2020, pp. 107555.
Elsevier DOI 2008
Multrenets, Auto-weighter, Separable MDLSTM, Multilingual handwritten text recognition, Multi-task learning BibRef

Mirza, A.[Ali], Siddiqi, I.[Imran],
Recognition of cursive video text using a deep learning framework,
IET-IPR(14), No. 14, December 2020, pp. 3444-3455.
DOI Link 2012
BibRef

Piot, M.[Melanie], Bourdoulous, B.[Berangere], Gonzalez, J.[Jordan], Deshayes, A.[Aurelia], Prevost, L.[Lionel],
Dual-Memory Model for Incremental Learning: The Handwriting Recognition Use Case,
ICPR21(5527-5534)
IEEE DOI 2105
Training, Handwriting recognition, Databases, Supervised learning, Training data, Psychology, Forestry, Incremental learning, handwriting recognition BibRef

Kang, L.[Lei], Riba, P.[Pau], Rusińol, M.[Marçal], Fornés, A.[Alicia], Villegas, M.[Mauricio],
Pay attention to what you read: Non-recurrent handwritten text-Line recognition,
PR(129), 2022, pp. 108766.
Elsevier DOI 2206
Handwriting text recognition, Transformers, Self-Attention, Implicit language model BibRef

Toiganbayeva, N.[Nazgul], Kasem, M.[Mahmoud], Abdimanap, G.[Galymzhan], Bostanbekov, K.[Kairat], Abdallah, A.[Abdelrahman], Alimova, A.[Anel], Nurseitov, D.[Daniyar],
KOHTD: Kazakh offline handwritten text dataset,
SP:IC(108), 2022, pp. 116827.
Elsevier DOI 2209
Document analysis and recognition, Handwritten Kazakh text recognition in Cyrillic, Deep learning BibRef

Kang, L.[Lei], Riba, P.[Pau], Rusińol, M.[Marçal], Fornés, A.[Alicia], Villegas, M.[Mauricio],
Content and Style Aware Generation of Text-Line Images for Handwriting Recognition,
PAMI(44), No. 12, December 2022, pp. 8846-8860.
IEEE DOI 2212
Visualization, Text recognition, Writing, Training, Handwriting recognition, Image recognition, Vocabulary, synthetic data generation BibRef

Coquenet, D.[Denis], Chatelain, C.[Clément], Paquet, T.[Thierry],
End-to-End Handwritten Paragraph Text Recognition Using a Vertical Attention Network,
PAMI(45), No. 1, January 2023, pp. 508-524.
IEEE DOI 2212
Text recognition, Hidden Markov models, Character recognition, Optical character recognition software, Image segmentation, optical character recognition BibRef

Xu, Z.Y.[Zhan-Yang], Qin, F.[Feiyang], Xiong, N.[Ningyang], Shi, H.Y.[Hong-Yan], Zhang, J.R.[Jia-Rui], Lin, W.[Wei],
Skeleton extraction of hard-pen regular script based on stroke characterization and ambiguous zone detection,
IET-IPR(18), No. 6, 2024, pp. 1504-1515.
DOI Link 2405
compensation, image processing, image restoration BibRef


Khanfir, Y.[Yessine], Dhiaf, M.[Marwa], Ghodhbani, E.[Emna], Rouhou, A.C.[Ahmed Cheikh], Kessentini, Y.[Yousri],
Graph Neural Networks for End-to-End Information Extraction from Handwritten Documents,
WACV24(493-501)
IEEE DOI 2404
Representation learning, Visualization, Text recognition, Noise, Computer architecture, Transformers, Information retrieval, Vision + language and/or other modalities BibRef

Retsinas, G.[George], Sfikas, G.[Giorgos], Nikou, C.[Christophoros], Maragos, P.[Petros],
Deformation-Invariant Networks for Handwritten Text Recognition,
ICIP21(949-953)
IEEE DOI 2201
Training, Handwriting recognition, Uncertainty, Image recognition, Text recognition, Writing, Handwritten Text Recognition, Spatial Transformer Network BibRef

Tassopoulou, V.[Vasiliki], Retsinas, G.[George], Maragos, P.[Petros],
Enhancing Handwritten Text Recognition with N-gram sequence decomposition and Multitask Learning,
ICPR21(10555-10560)
IEEE DOI 2105
Training, Text recognition, Computational modeling, Computer architecture, Network architecture, Decoding, Task analysis BibRef

Chao, L.L.[Lin-Lin], Chen, J.D.[Jing-Dong], Chu, W.[Wei],
Variational Connectionist Temporal Classification,
ECCV20(XXVIII:460-476).
Springer DOI 2011
Sequence labelling problems where the alignment between the inputs and the target labels is unknown. Otherwise, blank is the default. BibRef

Padilla, D.A., Vitug, N.K.U., Marquez, J.B.S.,
Deep Learning Approach in Gregg Shorthand Word to English-Word Conversion,
ICIVC20(204-210)
IEEE DOI 2009
Law, Training, Terminology, Testing, Feature extraction, Writing, Image Processing, TensorFlow, CNN, Inception-v3, Gregg Shorthand BibRef

Karimi, M., Veni, G., Yu, Y.,
Illegible Text to Readable Text: An Image-to-Image Transformation using Conditional Sliced Wasserstein Adversarial Networks,
WTDDL20(2353-2361)
IEEE DOI 2008
Generative adversarial networks, Handwriting recognition, Generators, Hidden Markov models, Text recognition BibRef

Nisa, H., Thom, J.A., Ciesielski, V., Tennakoon, R.,
A deep learning approach to handwritten text recognition in the presence of struck-out text,
IVCNZ19(1-6)
IEEE DOI 2004
convolutional neural nets, handwritten character recognition, learning (artificial intelligence), recurrent neural nets, Deep Learning BibRef

Bhunia, A.K.[Ayan Kumar], Das, A.[Abhirup], Bhunia, A.K.[Ankan Kumar], Kishore, P.S.R.[Perla Sai Raj], Roy, P.P.[Partha Pratim],
Handwriting Recognition in Low-Resource Scripts Using Adversarial Learning,
CVPR19(4762-4771).
IEEE DOI 2002
BibRef

Mirza, A.[Ali], Siddiqi, I.[Imran], Mustufa, S.G.[Syed Ghulam], Hussain, M.[Mazahir],
Impact of Pre-Processing on Recognition of Cursive Video Text,
IbPRIA19(I:565-576).
Springer DOI 1910
BibRef

Romero, V.[Verónica], Toselli, A.H.[Alejandro H.], Vidal, E.[Enrique], Sánchez, J.A.[Joan Andreu], Alonso, C.[Carlos], Marqués, L.[Lourdes],
Modern vs Diplomatic Transcripts for Historical Handwritten Text Recognition,
NTIAP19(103-114).
Springer DOI 1909
BibRef

Wigington, C.[Curtis], Tensmeyer, C.[Chris], Davis, B.[Brian], Barrett, W.[William], Price, B.L.[Brian L.], Cohen, S.[Scott],
Start, Follow, Read: End-to-End Full-Page Handwriting Recognition,
ECCV18(VI: 372-388).
Springer DOI 1810
BibRef

Suwanwiwat, H.[Hemmaphan], Pal, U.[Umapada], Blumenstein, M.[Michael],
An Automatic Off-Line Short Answer Assessment System Using Novel Hybrid Features,
DICTA16(1-8)
IEEE DOI 1701
BibRef
Earlier: A1, A3, A2:
A complete automatic short answer assessment system with student identification,
ICDAR15(611-615)
IEEE DOI 1511
Artificial neural networks. Enhanced Water Reservoir. Automatic assessment with handwriting recognition. BibRef

Yousefi, M.R.[Mohammad Reza], Soheili, M.R.[Mohammad Reza], Breuel, T.M.[Thomas M.], Kabir, E.[Ehsanollah], Stricker, D.[Didier],
Binarization-free OCR for historical documents using LSTM networks,
ICDAR15(1121-1125)
IEEE DOI 1511
BibRef

Sanchez, J.A.[Joan Andreu], Toselli, A.H.[Alejandro H.], Romero, V.[Veronica], Vidal, E.[Enrique],
ICDAR 2015 competition HTRtS: Handwritten Text Recognition on the tranScriptorium dataset,
ICDAR15(1166-1170)
IEEE DOI 1511
Handwritten Text Recognition;Historical Documents BibRef

Villegas, M.[Mauricio], Sanchez, J.A.[Joan Andreu], Vidal, E.[Enrique],
Optical modelling and language modelling trade-off for Handwritten Text Recognition,
ICDAR15(831-835)
IEEE DOI 1511
Handwritten Text Recognition BibRef

Frinken, V.[Volkmar], Uchida, S.[Seiichi],
Deep BLSTM neural networks for unconstrained continuous handwritten text recognition,
ICDAR15(911-915)
IEEE DOI 1511
BibRef

Zhang, X.[Xiong], Wang, M.[Min], Wang, L.J.[Li-Juan], Huo, Q.A.[Qi-Ang], Li, H.F.[Hai-Feng],
Building Handwriting Recognizers by Leveraging Skeletons of Both Offline and Online Samples,
ICDAR15(406-410)
IEEE DOI 1511
BibRef

Chen, K.[Kai], Yan, Z.J.[Zhi-Jie], Huo, Q.A.[Qi-Ang],
A context-sensitive-chunk BPTT approach to training deep LSTM/BLSTM recurrent neural networks for offline handwriting recognition,
ICDAR15(411-415)
IEEE DOI 1511
BibRef

Kakisako, R.[Ryosuke], Uchida, S.[Seiichi], Volkmar, F.[Frinken],
Learning non-Markovian constraints for handwriting recognition,
ICDAR15(446-450)
IEEE DOI 1511
BibRef

Liu, Q.[Qi], Wang, L.J.[Li-Juan], Huo, Q.A.[Qi-Ang],
A study on effects of implicit and explicit language model information for DBLSTM-CTC based handwriting recognition,
ICDAR15(461-465)
IEEE DOI 1511
BibRef

Mioulet, L.[Luc], Garain, U.[Utpal], Chatelain, C.[Clement], Barlas, P.[Philippine], Paquet, T.[Thierry],
Language identification from handwritten documents,
ICDAR15(676-680)
IEEE DOI 1511
BLSTM-CTC BibRef

Bluche, T.[Theodore], Kermorvant, C.[Christopher], Louradour, J.[Jerome],
Where to apply dropout in recurrent neural networks for handwriting recognition?,
ICDAR15(681-685)
IEEE DOI 1511
BibRef

Boukerma, H.[Hanene], Benouareth, A.[Abdallah], Farah, N.[Nadir],
NSHP-HMM Based on Conditional Zone Observation Probabilities for Off-Line Handwriting Recognition,
ICPR14(2961-2965)
IEEE DOI 1412
Computational modeling BibRef

Dahllof, M.[Mats],
Scribe Attribution for Early Medieval Handwriting by Means of Letter Extraction and Classification and a Voting Procedure for Larger Pieces,
ICPR14(1910-1915)
IEEE DOI 1412
Accuracy BibRef

Bideault, G.[Gautier], Mioulet, L.[Luc], Chatelain, C.[Clément], Paquet, T.[Thierry],
A Hybrid CRF/HMM Approach for Handwriting Recognition,
ICIAR14(I: 403-410).
Springer DOI 1410
BibRef

Schambach, M.P., Rashid, S.F.,
Stabilize Sequence Learning with Recurrent Neural Networks by Forced Alignment,
ICDAR13(1270-1274)
IEEE DOI 1312
Neural Networks for cursive scripts. BibRef

Hamdani, M.[Mahdi], Doetsch, P.[Patrick], Ney, H.[Hermann],
Bagging by design for continuous Handwriting Recognition using multi-objective particle swarm optimization,
ICDAR15(256-260)
IEEE DOI 1511
BibRef

Kozielski, M., Doetsch, P.[Patrick], Ney, H.[Hermann],
Improvements in RWTH's System for Off-Line Handwriting Recognition,
ICDAR13(935-939)
IEEE DOI 1312
feature extraction BibRef

Shivram, A., Ramaiah, C., Setlur, S., Govindaraju, V.,
IBM_UB_1: A Dual Mode Unconstrained English Handwriting Dataset,
ICDAR13(13-17)
IEEE DOI 1312
Dataset, OCR. handwriting recognition BibRef

Puri, M., Srihari, S.N., Tang, Y.[Yi],
Bayesian Network Structure Learning and Inference Methods for Handwriting,
ICDAR13(1320-1324)
IEEE DOI 1312
belief networks BibRef

Mizukami, Y.[Yoshiki], Nakanishi, S.[Shinya],
Performance Study of a Regularization-Based Deformable Handwritten Recognition Approach,
CIAP13(I:300-309).
Springer DOI 1311
BibRef

Gur, E.[Eran], Zelavsky, Z.[Zeev],
Retrieval of Rashi Semi-cursive Handwriting via Fuzzy Logic,
FHR12(354-359).
IEEE DOI 1302
BibRef

Furukawa, T.[Takeshi],
The New Method of Identification of Handwriting Using Volumes of Indentations,
FHR12(163-168).
IEEE DOI 1302
BibRef

Chen, J.[Jin], Zhang, B.[Bing], Cao, H.[Huaigu], Prasad, R.[Rohit], Natarajan, P.[Prem],
Applying Discriminatively Optimized Feature Transform for HMM-based Off-Line Handwriting Recognition,
FHR12(219-224).
IEEE DOI 1302
BibRef

Czúni, L.[László], Szöke, T.[Tamás], Gál, M.[Mónika],
Recognition of Hand-Written Archive Text Documents,
ICCVG12(337-344).
Springer DOI 1210
BibRef

Dreuw, P.[Philippe], Doetsch, P.[Patrick], Plahl, C.[Christian], Ney, H.[Hermann],
Hierarchical hybrid MLP/HMM or rather MLP features for a discriminatively trained Gaussian HMM: A comparison for offline handwriting recognition,
ICIP11(3541-3544).
IEEE DOI 1201

See also Enhanced continuous sign language recognition using PCA and neural network features. BibRef

Parziale, A.[Antonio], Fuschetto, S.G.[Salvatore G.], Marcelli, A.[Angelo],
Exploiting Stability Regions for Online Signature Verification,
EAHSP13(112-121).
Springer DOI 1309
BibRef

Cordella, L.P., de Stefano, C., Fontanella, F., Scotto di Freca, A.,
Random Forest for Reliable Pre-classification of Handwritten Characters,
ICPR14(1319-1324)
IEEE DOI 1412
Error analysis BibRef

de Stefano, C.[Claudio], Marcelli, A.[Angelo], Parziale, A.[Antonio], Senatore, R.[Rosa],
Reading Cursive Handwriting,
FHR10(95-100).
IEEE DOI 1011
BibRef

Senatore, R.[Rosa], Marcelli, A.[Angelo],
A Neural Scheme for Procedural Motor Learning of Handwriting,
FHR12(659-664).
IEEE DOI 1302
BibRef

Cordella, L.P.[Luigi P.], de Stefano, C.[Claudio], Marcelli, A.[Angelo], Santoro, A.[Adolfo],
Writing Order Recovery from Off-Line Handwriting by Graph Traversal,
ICPR10(1896-1899).
IEEE DOI 1008
BibRef

Ball, G.R.[Gregory R.], Srihari, S.N.[Sargur N.],
Semi-supervised Learning for Handwriting Recognition,
ICDAR09(26-30).
IEEE DOI 0907
BibRef

Fischer, A.[Andreas], Bunke, H.[Horst],
Kernel PCA for HMM-Based Cursive Handwriting Recognition,
CAIP09(181-188).
Springer DOI 0909
BibRef

Do, T.M.T.[Trinh-Minh-Tri], Artičres, T.[Thierry],
Maximum Margin Training of Gaussian HMMs for Handwriting Recognition,
ICDAR09(976-980).
IEEE DOI 0907
BibRef

Wang, Y.Q.[Yong-Qiang], Liu, P.[Peng], Huo, Q.A.[Qi-Ang],
An ellipsoid constrained quadratic programming (ECQP) approach to MCE training of MQDF-based classifiers for handwriting recognition,
ICPR08(1-4).
IEEE DOI 0812
BibRef

Niels, R., Vuurpijl, L.,
Generating Copybooks from Consistent Handwriting Styles,
ICDAR07(1009-1013).
IEEE DOI 0709
BibRef

Fink, G.A., Plotz, T.,
On the Use of Context-Dependent Modeling Units for HMM-Based Offline Handwriting Recognition,
ICDAR07(729-733).
IEEE DOI 0709
BibRef

Ye, M., Viola, P., Raghupathy, S., Sutanto, H., Li, C.,
Learning to Group Text Lines and Regions in Freeform Handwritten Notes,
ICDAR07(28-32).
IEEE DOI 0709
BibRef

Ye, M., Sutanto, H., Raghupathy, S., Li, C., Shilman, M.,
Grouping text lines in freeform handwritten notes,
ICDAR05(I: 367-371).
IEEE DOI 0508
BibRef

Shilman, M.[Michael], Wei, Z.[Zile],
Recognizing Freeform Digital Ink Annotations,
DAS04(322-331).
Springer DOI 0505
BibRef

Shilman, M., Wei, Z.[Zile], Raghupathy, S., Simard, P.Y., Jones, D.,
Discerning structure from freeform handwritten notes,
ICDAR03(60-65).
IEEE DOI 0311
BibRef

Pan, W.M., Suen, C.Y.[Ching Y.], Bui, T.D.[Tien D.],
Script identification using steerable Gabor filters,
ICDAR05(II: 883-887).
IEEE DOI 0508
BibRef

Htwe, S.M.[Swe Myo], Higgins, C.[Colin], Leedham, G.[Graham], Yang, M.[Ma],
Post-processing of Handwritten Pitman's Shorthand Using Unigram and Heuristic Approaches,
DAS04(332-336).
Springer DOI 0505
BibRef

Lemaitre, M.[Melanie], Grosicki, E.[Emmanuele], Preteux, F.[Francoise],
Preliminary experiments in layout analysis of handwritten letters based on textural and spatial information and a 2D Markovian approach,
ICDAR07(1023-1027).
IEEE DOI 0709
BibRef

Chevalier, S., Geoffrois, E., Preteux, F.J., Lemaitre, M.,
A generic 2D approach of handwriting recognition,
ICDAR05(I: 489-493).
IEEE DOI 0508
BibRef

Pervouchine, V., Leedham, G., Melikhov, K.,
Three-stage handwriting stroke extraction method with hidden loop recovery,
ICDAR05(I: 307-311).
IEEE DOI 0508
BibRef

Long, T.[Teng], Jin, L.W.[Lian-Wen],
Hybrid recognition for one stroke style cursive handwriting characters,
ICDAR05(I: 232-236).
IEEE DOI 0508
BibRef

Senda, S., Yamada, K.,
A maximum-likelihood approach to segmentation-based recognition of unconstrained handwriting text,
ICDAR01(184-188).
IEEE DOI 0109
BibRef

Evreinov, G.[Grigori], Raisamo, R.[Roope],
Rapid Evaluation of the Handwriting Performance for Gesture Based Text Input,
GW05(339-342).
Springer DOI 0505
BibRef

Lau, K.K., Yuen, P.C., Tang, Y.Y.,
Recovery of writing sequence of static images of handwriting using UWM,
ICDAR03(1123-1128).
IEEE DOI 0311
BibRef

Ruiz-Pinales, J., Lecolinet, E.,
A new perceptive system for the recognition of cursive handwriting,
ICPR02(III: 53-56).
IEEE DOI 0211
BibRef

Vuori, V.,
Clustering writing styles with a self-organizing map,
FHR02(345-350).
IEEE Top Reference. 0209
BibRef

Tomai, C.I., Zhang, B.[Bin], Govindaraju, V.,
Transcript mapping for historic handwritten document images,
FHR02(413-418).
IEEE Top Reference. 0209
BibRef

Park, J.S., Kang, H.J., Lee, S.W.,
Automatic Quality Measurement of Gray-scale Handwriting Based on Extended Average Entropy,
ICPR00(Vol IV: 426-429).
IEEE DOI 0009
BibRef

Veloso, L.R.[Luciana Ribeiro], de Sousa, R., de Carvalho, J.M.[Joao Marques],
A New Morphological Method for Cursive Word Segmentation,
ICIP00(Vol II: 704-707).
IEEE DOI 0008
BibRef

Ruiz-Pinales, J., Lecolinet, E.,
Cursive Handwriting Recognition Using the Hough Transform and a Neural Network,
ICPR00(Vol II: 231-234).
IEEE DOI 0009
BibRef

Scagliola, C., Nicchiotti, G.,
Crisp and Fuzzy Evaluations and D.P. Algorithms for Dealing with Extra Ink in Cursive Handwriting Recognition,
ICPR00(Vol IV: 19-22).
IEEE DOI 0009
BibRef

Yamada, K.[Keiji],
Handwritten Text Retrieval Using Two-Stage Pattern Matching with Handwritten Query,
ICPR98(Vol I: 621-625).
IEEE DOI 9808
BibRef

Wakahara, T.[Toru], Ogura, K.[Kenji],
Extended Mean Shift in Handwriting Clustering,
ICPR98(Vol I: 384-388).
IEEE DOI 9808
BibRef

Franke, J., Gloger, J.M., Kaltenmeier, A., Mandler, E.,
A Comparison of Gaussian Distribution and Polynomial Classifiers in a Hidden Markov Model Based System for the Recognition of Cursive Script,
ICDAR97(515-518).
IEEE DOI 9708
BibRef

Jaeger, S.,
A Psychomotor Method For Tracking Handwriting,
ICDAR97(528-531).
IEEE DOI 9708
BibRef

Jaeger, S.,
Recovering Dynamic Information from Static, Handwritten Word Images,
Ph.D.Thesis, 1998. BibRef 9800

Jaeger, S.,
Recovering Writing Traces in Off-Line Handwriting Recognition: Using a Global Optimization Technique,
ICPR96(III: 150-154).
IEEE DOI 9608
(Daimler-Benz AG, D) BibRef

Yanikoglu, B.A., Sandon, P.A.,
Recognizing Off-Line Cursive Handwriting,
CVPR94(397-403).
IEEE DOI Cursive Script. BibRef 9400

Navarro, A., Allen, C.R.[Charles R.],
Towards a writer-dependent hand-written character recogniser,
ICIP96(II: 189-192).
IEEE DOI BibRef 9600

Stettiner, O., Chazan, D.,
A statistical parametric model for recognition and synthesis of handwriting,
ICPR94(B:34-38).
IEEE DOI 9410
BibRef

Higgins, C.A., Ford, D.M.,
Online recognition of connected handwriting by segmentation and template matching,
ICPR92(II:200-203).
IEEE DOI 9208
BibRef

Singer, Y., Tisby, N.,
Dynamical encoding of cursive handwriting,
CVPR93(341-346).
IEEE DOI 0403
BibRef

Kondo, S., Maitree, K., Itoh, D., Atsuta, K.,
Structure analysis of handwriting using opposing relations,
ICPR92(II:529-532).
IEEE DOI 9208
BibRef

Kondo, S., Attachoo, B.,
Model of Handwriting Process and Its Analysis,
ICPR86(562-565). BibRef 8600

Nag, R., Wong, K.H., and Fallside, F.,
Script Recognition Using Hidden Markov Models,
ICASSP86(2071-2074). BibRef 8600

Lecolinet, E., Crettez, J.P.,
A Grapheme-Based Segmentation Technique for Cursive Script Recognition,
ICDAR91(740-xx). BibRef 9100

Wong, K.H., Fallside, F.,
Dynamic Programming in the Recognition of Connected Handwritten Script,
CAIA85(666-670). BibRef 8500

Sinha, R.M.K.,
A Knowledge Based Script Reader,
ICPR84(763-765). BibRef 8400

Chapter on OCR, Document Analysis and Character Recognition Systems continues in
Cursive Script, Word Level Recognition, Word Spotting, Language Model .


Last update:Oct 22, 2024 at 22:09:59