Handwritten Characters, Roman, Latin Alphabet

Chapter Contents (Back)
Printed Characters. Handwriting.

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Kovacs-Vajna, Z.M., Guerrieri, R.,
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Kovacs-Vajna, Z.M.,
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Shustorovich, A., Thrasher, C.W.,
Neural-Network Positioning and Classification of Handwritten Characters,
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Earlier: ICPR96(D82.9). 9608
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AbuHaiba, I.S.I., Holt, M.J.J., Datta, S.,
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AbuHaiba, I.S.I., Datta, S., Holt, M.J.J.,
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AbuHaiba, I.S.I., Holt, M.J.J., Datta, S.,
Processing of Binary Images of Handwritten Text Documents,
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Kim, D.H., Kim, E.J., Bang, S.Y.,
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Fairhurst, M.C., Rahman, A.F.R.,
Generalized-Approach to the Recognition of Structurally Similar Handwritten Characters Using Multiple Expert Classifiers,
VISP(144), No. 1, February 1997, pp. 15-22. 9706
Classifiers, multiple. See also New Hybrid Approach in Combining Multiple Experts to Recognize Handwritten Numerals, A. See also Design Considerations in the Real-Time Implementation of Multiple Expert Image Classifiers within a Modular and Flexible Multiple-platform Design Environment. BibRef

Cheng, D.H., Yan, H.,
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Fan, K.C., Wang, Y.K.,
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Garris, M.D., Blue, J.L., Candela, G.T., Dimmick, D.L., Geist, J.C., Grother, P.J., Janet, S.A., Wilson, C.L.,
Off-line Handwriting Recognition from Forms,
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Garris, M.D., Wilson, C.L., Blue, J.L.,
Neural Network Based Systems for Handprint OCR Applications,
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IEEE DOI Link 9808

Heutte, L., Paquet, T., Moreau, J.V., Lecourtier, Y., Olivier, C.,
A Structural/Statistical Feature Based Vector for Handwritten Character Recognition,
PRL(19), No. 7, May 1998, pp. 629-641. 9808
Earlier: A1, A3, A2, A4, A5:
Combining Structural and Statistical Features for the Recognition of Handwritten Characters,
ICPR96(II: 210-214).
IEEE DOI Link 9608
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Wada, K., Mori, K., Toraichi, K.,
PARM: A Parallel Relaxation Machine for Handwritten Character Recognition,
PRL(19), No. 5-6, April 1998, pp. 475-481. 9808

Chim, Y.C.[Yuen-Chong], Kassim, A.A.[Ashraf A.], Ibrahim, Y.[Yaacob],
Dual Classifier System for Handwritten Alphanumeric Character Recognition,
PAA(1), No. 3, 1998, pp. xx-yy. BibRef 9800

Oh, I.S.[Il-Seok], Suen, C.Y.[Ching Y.],
Distance features for neural network-based recognition of handwritten characters,
IJDAR(1), No. 2, 1998, pp. 319-330. BibRef 9800
A Feature for Character Recognition Based on Directional Distance Distributions,
IEEE DOI Link 9708

Oh, I.S.[Il-Seok], Suen, C.Y.[Ching Y.],
A class-modular feedforward neural network for handwriting recognition,
PR(35), No. 1, January 2002, pp. 229-244.
WWW Version. 0111

Oh, I.S.[Il-Seok], Lee, J.S.[Jin-Seon], Suen, C.Y.[Ching Y.],
Analysis of Class Separation and Combination of Class-Dependent Features for Handwriting Recognition,
PAMI(21), No. 10, October 1999, pp. 1089-1094.
IEEE DOI Link BibRef 9910
A class-modularity for character recognition,
IEEE DOI Link 0109
Feature-Selection-Based combination and class-dependent features. BibRef

Lee, J.S.[Jin-Seon], Suen, C.Y.[Ching Y.], Oh, I.S.[Il-Seok],
Using Class Separation for Feature Analysis and Combination of Class-Dependent Features,
ICPR98(Vol I: 453-455).
IEEE DOI Link 9808

Li, Z.C., Suen, C.Y.,
The partition-combination method for recognition of handwritten characters,
PRL(21), No. 6-7, June 2000, pp. 701-720. 0006

Li, Z.C., Suen, C.Y.,
Crucial combinations for the recognition of handwritten letters,
PRL(21), No. 10, October 2000, pp. 873-898. 0008

Chen, H., Agazzi, O.E., Suen, C.Y.,
Piecewise Linear Modulation Model of Handwriting,
IEEE DOI Link 9708

Chen, W., Suen, C.Y., Strobel, M.G.,
Extraction of Lines of Texts in Unconstrained Handwritten Documents,
ICDAR97(We-1A) 9708
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Ghosh, D., Shivaprasad, A.P.,
An analytic approach for generation of artificial hand-printed character database from given generative models,
PR(32), No. 6, June 1999, pp. 907-920.
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Pessoa, L.F.C.[Lúcio F.C.], Maragos, P.[Petros],
Neural networks with hybrid morphological/rank/linear nodes: a unifying framework with applications to handwritten character recognition,
PR(33), No. 6, June 2000, pp. 945-960.
WWW Version. 0004

Lazzerini, B.[Beatrice], Marcelloni, F.[Francesco],
A linguistic fuzzy recogniser of off-line handwritten characters,
PRL(21), No. 3, March 2000, pp. 319-327. 0004

de Stefano, C., della Cioppa, A., Marcelli, A.,
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PRL(23), No. 12, October 2002, pp. 1439-1448.
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Cordella, L.P., de Stefano, C., Fontanella, F., Marrocco, C.,
A feature selection algorithm for handwritten character recognition,
IEEE DOI Link 0812

Cordella, L.P., de Stefano, C., Fontanella, F., Marcelli, A.,
Looking for Prototypes by Genetic Programming,
Springer DOI Link 0608
A Novel Genetic Programming Based Approach for Classification Problems,
Springer DOI Link 0509

Cordella, L.P., Foggia, P., Sansone, C., Tortorella, F., Vento, M.,
Prototyping Structural Shape Descriptions by Inductive Learning,
VF01(484 ff.).
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de Stefano, C.[Claudio], della Cioppa, A., Marcelli, A., Matarazzo, F.,
Grouping Character Shapes by Means of Genetic Programming,
VF01(504 ff.).
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de Stefano, C., della Cioppa, A., Marcelli, A.,
Learning handwriting by evolution: a conceptual framework for performance evaluation and tuning,
PR(35), No. 5, May 2002, pp. 1025-1037.
WWW Version. 0202

de Stefano, C.[Claudio], Garruto, M.[Marco], Lapresa, L.[Luis], Marcelli, A.[Angelo],
Using Strings for On-Line Handwriting Shape Matching: A New Weighted Edit Distance,
Springer DOI Link 0509

de Stefano, C., Garruto, M., Marcelli, A.,
A multiresolution approach to on-line handwriting segmentation and feature extraction,
ICPR04(II: 614-617).
IEEE DOI Link 0409

Hanmandlu, M., Murali Mohan, K.R., Chakraborty, S.[Sourav], Goyal, S.[Sumeer], Choudhury, D.R.[D. Roy],
Unconstrained handwritten character recognition based on fuzzy logic,
PR(36), No. 3, March 2003, pp. 603-623.
WWW Version. 0301

Hanmandlu, M., Mohan, K., Chakraborty, S., Goel, S.,
Fuzzy Logic Based Handwritten Character Recognition,
ICIP01(III: 42-45).
IEEE DOI Link 0108

Hanmandlu, M., Murali Mohan, K.R., Gupta, V.,
Fuzzy Logic Based Handwritten Character Recognition 2,
ICIP97(III: 714-717).
IEEE DOI Link 9710

Chakravarthy, V.S.[V. Srinivasa], Kompella, B.[Bhaskar],
The shape of handwritten characters,
PRL(24), No. 12, August 2003, pp. 1901-1913.
WWW Version. 0304

Gangadhar, G.[Garipelli], Joseph, D.[Denny], Chakravarthy, V.S.[V. Srinivasa],
An oscillatory neuromotor model of handwriting generation,
IJDAR(10), No. 2, November 2007, pp. 69-84.
Springer DOI Link 0711

Aksela, M.[Matti], Girdziusas, R.[Ramunas], Laaksonen, J.T.[Jorma T.], Oja, E.[Erkki], Kangas, J.[Jari],
Methods for adaptive combination of classifiers with application to recognition of handwritten characters,
IJDAR(6), No. 1, 2003, pp. 23-41.
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Aksela, M.[Matti], Laaksonen, J.T.[Jorma T.], Oja, E., Kangas, J.,
Rejection methods for an adaptive committee classifier,
IEEE DOI Link 0109

Aksela, M.[Matti], Laaksonen, J.T.[Jorma T.],
Adaptive combination of adaptive classifiers for handwritten character recognition,
PRL(28), No. 1, 1 January 2007, pp. 136-143.
WWW Version. 0611
Classifier combining; Adaptive classifiers; Adaptive committee; On-line adaptation; Handwritten character recognition BibRef

Chou, C.H.[Chien-Hsing], Lin, C.C.[Chin-Chin], Liu, Y.H.[Ying-Ho], Chang, F.[Fu],
A prototype classification method and its use in a hybrid solution for multiclass pattern recognition,
PR(39), No. 4, April 2006, pp. 624-634.
WWW Version. 0604
Fuzzy c-means clustering algorithm; Handwritten character recognition; Hybrid classifier; K-means clustering algorithm; Prototype learning; Support vector machine BibRef

Oncina, J.[Jose], Sebban, M.[Marc],
Learning stochastic edit distance: Application in handwritten character recognition,
PR(39), No. 9, September 2006, pp. 1575-1587.
WWW Version. 0606
Using Learned Conditional Distributions as Edit Distance,
Springer DOI Link 0608
Stochastic edit distance; Finite-state transducers See also Learning state machine-based string edit kernels. BibRef

Micó, L.[Luisa], Oncina, J.[Jose],
A log square average case algorithm to make insertions in fast similarity search,
PRL(33), No. 9, 1 July 2012, pp. 1060-1065.
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Similarity search; Metric space; Dynamic index; Insertions BibRef

Gagné, C.[Christian], Parizeau, M.[Marc],
Genetic engineering of hierarchical fuzzy regional representations for handwritten character recognition,
IJDAR(8), No. 4, September 2006, pp. 223-231.
Springer DOI Link 0609

Lemieux, A., Gagné, C.[Christian], Parizeau, M.[Marc],
Genetical engineering of handwriting representations,
IEEE Top Reference. 0209

Parizeau, M., Lemieux, A., Gagne, C.,
Character recognition experiments using Unipen data,
IEEE DOI Link 0109

Plötz, T.[Thomas], Fink, G.A.[Gernot A.],
Markov models for offline handwriting recognition: a survey,
IJDAR(12), No. 4, December 2009, pp. xx-yy.
Springer DOI Link 0912
Survey, Handwriting. BibRef

Pauplin, O.[Olivier], Jiang, J.M.[Jian-Min],
DBN-based structural learning and optimisation for automated handwritten character recognition,
PRL(33), No. 6, 15 April 2012, pp. 685-692.
Elsevier DOI Link 1203
Pattern classification; Dynamic Bayesian Network; Structure learning; Supervised learning; Handwritten character recognition; Evolutionary Algorithm BibRef

Liwicki, M.[Marcus], Ebert, S.[Sebastian], Dengel, A.[Andreas],
Bridging the gap between handwriting recognition and knowledge management,
PRL(35), No. 1, 2014, pp. 204-213.
Elsevier DOI Link 1312
Handwriting recognition BibRef

Cecotti, H., Vajda, S.,
A Radial Neural Convolutional Layer for Multi-oriented Character Recognition,
IEEE DOI Link 1312
Rejection Schemes in Multi-class Classification: Application to Handwritten Character Recognition,
IEEE DOI Link 1312
handwritten character recognition Radon transforms. BibRef

Roy, U., Sankaran, N., Sankar, K.P., Jawahar, C.V.,
Character N-Gram Spotting on Handwritten Documents Using Weakly-Supervised Segmentation,
IEEE DOI Link 1312
handwritten character recognition BibRef

Breuel, T.M., Ul-Hasan, A., Al-Azawi, M.A., Shafait, F.,
High-Performance OCR for Printed English and Fraktur Using LSTM Networks,
IEEE DOI Link 1312
handwriting recognition BibRef

Hirabara, L.Y.[Luciane Y.], Aires, S.B.K.[Simone B.K.], Freitas, C.O.A.[Cinthia O.A.], de Souza Britto, A.[Alceu], Sabourin, R.[Robert],
Dynamic Zoning Selection for Handwritten Character Recognition,
Springer DOI Link 1111

Ciresan, D.C.[Dan Claudiu], Meier, U.[Ueli], Gambardella, L.M.[Luca Maria], Schmidhuber, J.[Jurgen],
Convolutional Neural Network Committees for Handwritten Character Classification,
IEEE DOI Link 1111

Gao, Y.[Yan], Jin, L.[Lanwen], He, C.[Cong], Zhou, G.[Guibin],
Handwriting Character Recognition as a Service: A New Handwriting Recognition System Based on Cloud Computing,
IEEE DOI Link 1111

Miyoshi, T.[Toshinori], Shinjo, H.[Hiroshi], Nagasaki, T.[Takeshi],
Simplified polynomial network classifier for handwritten character recognition,
IEEE DOI Link 0812

Schlapbach, A.[Andreas], Wettstein, F.[Frank], Bunke, H.[Horst],
Estimating the readability of handwritten text: A Support Vector Regression based approach,
IEEE DOI Link 0812

Thome, N., Vacavant, A.,
A Combined Statistical-Structural Strategy for Alphanumeric Recognition,
ISVC07(II: 529-538).
Springer DOI Link 0711

Sadri, J.[Javad], Suen, C.Y.[Ching Y.], Bui, T.D.[Tien D.],
A New Clustering Method for Improving Plasticity and Stability in Handwritten Character Recognition Systems,
ICPR06(II: 1130-1133).
IEEE DOI Link 0609

Miyao, H.[Hidetoshi], Maruyama, M.[Minoru],
Virtual Example Synthesis Based on PCA for Off-Line Handwritten Character Recognition,
Springer DOI Link 0602
See also online handwritten music symbol recognition system, An. See also On-Line Handwritten flowchart Recognition, Beautification and Editing System. BibRef

Miyao, H., Maruyama, M., Nakano, Y., Hananoi, T.,
Off-line handwritten character recognition by SVM based on the virtual examples synthesized from on-line characters,
ICDAR05(I: 494-498).
IEEE DOI Link 0508

Liu, Y.[Yang], Liu, X.B.[Xia-Bi], Jia, Y.D.[Yun-De],
Hand-Gesture Based Text Input for Wearable Computers,
IEEE DOI Link 0602
Write the character by the fingertip. BibRef

Keysers, D., Gollan, C., Ney, H.,
Local context in non-linear deformation models for handwritten character recognition,
ICPR04(IV: 511-514).
IEEE DOI Link 0409

Sun, G.[Guangling], Huang, J.H.[Jian-Hua], Tang, X.L.[Xiang-Long],
Active discriminant functions for handwriting recognition,
ICPR04(II: 602-605).
IEEE DOI Link 0409

Chang, F.[Fu], Lin, C.C.[Chin-Chin], Chen, C.J.[Chun-Jen],
Applying a hybrid method to handwritten character recognition,
ICPR04(II: 529-532).
IEEE DOI Link 0409

Noor, N.M., Razaz, M., Manley-Cooke, P.,
Global geometry extraction for fuzzy logic based handwritten character recognition,
ICPR04(II: 513-516).
IEEE DOI Link 0409

Ellozy, H.A.[Hamed A.], Jeanty, H.H.[Henry H.], Tappert, C.C.[Charles C.],
Handwriting recognition employing pairwise discriminant measures,
US_Patent5,005,205, April 2, 1991.
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Cha, S.H.[Sung-Hyuk], Yoon, S.S.[Sung-Soo], Tappert, C.C.,
On binary similarity measures for handwritten character recognition,
ICDAR05(I: 4-8).
IEEE DOI Link 0508

Cha, S.H.[Sung-Hyuk], Tappert, C.C., Srihari, S.N.,
Optimizing binary feature vector similarity measure using genetic algorithm and handwritten character recognition,
IEEE Abstract. 0311

Feldbach, M., Tönnies, K.D.,
Word segmentation of handwritten dates in historical documents by combining semantic a-priori-knowledge with local features,
IEEE Abstract. 0311
Segmentation of the Date in Entries of Historical Church Registers,
DAGM02(403 ff.).
HTML Version. 0303
Line detection and segmentation in historical church registers,
IEEE DOI Link 0109

Cho, S.J.[Sung-Jung], Perrone, M.P., Ratzlaff, E.,
Probability table compression for handwritten character recognition,
IEEE Abstract. 0311

Nopsuwanchai, R., Povey, D.,
Discriminative training for HMM-based of fine handwritten character recognition,
IEEE Abstract. 0311

Wada, Y., Kasuga, H., Sumita, K.,
An evolutionary approach for the generation of diversiform characters using a handwriting model,
ICPR02(III: 131-134).
IEEE DOI Link 0211

Mori, M.,
Video text recognition using feature compensation as category-dependent feature extraction,
IEEE Abstract. 0311

Mori, M., Sawaki, M., Hagita, N.,
Category-dependent feature extraction for recognition of degraded handwritten characters,
ICPR02(III: 155-159).
IEEE DOI Link 0211

Mori, M., Sawaki, M., Hagita, N., Murase, H., Mukawa, N.,
Robust feature extraction based on run-length compensation for degraded handwritten character recognition,
IEEE DOI Link 0109

Lam, L., Xu, Q.[Qizhi], Suen, C.Y.,
Differentiation between alphabetic and numeric data using NN ensembles,
ICPR02(IV: 40-43).
IEEE DOI Link 0211

Zhu, X.Y.[Xiao-Yan], Shi, Y.[Yifan],
A handwritten character recognition method with ANN feedback,
IEEE DOI Link 0109
A New Algorithm for Handwritten Character Recognition,
ICIP01(I: 1130-1133).
IEEE DOI Link 0108

Arlandis, J.[Joaquim], Perez-Cortes, J.C.[Juan-Carlos], Llobet, R.[Rafael],
Handwritten Character Recognition Using the Continuos Distance Transformation,
ICPR00(Vol I: 940-943).
IEEE DOI Link 0009

Miller, E.G.[Erik G.], Matsakis, N.E.[Nicholas E.], Viola, P.A.[Paul A.],
Learning from One Example through Shared Densities on Transforms,
CVPR00(I: 464-471).
IEEE DOI Link 0005
Learning BibRef

Prema, K.V., Reddy, N.V.S.,
Neural Network Based Handwritten Character Recognition for Conflict Resolution,
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Waizumi, Y., Kato, N., Saruta, K., Nemoto, Y.,
High Speed Rough Classification for Handwritten Characters Using Hierarchical Learning Vector Quantization,
IEEE DOI Link 9708

Matsumura, S., Kobayashi, T., Nakamura, O., Ogura, K.,
Document Input According to Recognition Accuracy of Handwritten Characters,
IEEE DOI Link 9708

Rodrigues Gomes, N., Lee, L.L.[Luan Ling],
Feature extraction based on fuzzy set theory for handwriting recognition,
IEEE DOI Link 0109

Lee, L.L.[Luan Ling], Rodrigues Gomes, N.,
Disconnected Handwritten Character Image Recognition,
IEEE DOI Link 9708

Gloger, J.M., Kaltenmeier, A., Mandler, E., Andrews, L.,
Reject Management in a Handwriting Recognition System,
IEEE DOI Link 9708

Kimura, F., Kayahara, N., Miyake, Y., Shridhar, M.,
Machine and human recognition of segmented characters from handwritten words,
IEEE DOI Link 9708

Park, H.S.[Hee-Seon], Lee, S.W.[Seong-Whan],
An HMMRF-based statistical approach for off-line handwritten character recognition,
ICPR96(II: 320-324).
IEEE DOI Link 9608
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Gong, Y., Boyer, A.,
Hand-written text recognition based on a new formulation,
IEEE DOI Link 9208

Yokozuka, S., Kida, H.,
An application of feature selection to handwritten character recognition,
IEEE DOI Link 9208

Kimura, M., Ejima, T., Aso, H., Yashiro, H., Son, N., Suzuki, M.,
An Intelligent Character Recognition System with High Accuracy and High Speed by Integrating Image-Type and Logical-Type Information Processings,
ICPR88(I: 38-40).
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Holder, S., Dengler, J.,
Font- and Size-Invariant Character Recognition with Greyvalue Image Features,
ICPR88(I: 252-254).
IEEE DOI Link 8811

Leveridge, P.C., Leedham, C.G.,
Experiments with an N-Tuple Recogniser for Fast 'First Try' Recognition of Unconstrained Handwritten Symbols,
ICPR88(II: 905-907).
IEEE DOI Link 8811

Lettera, C., Masera, L., Paoli, C., Porinelli, R.,
Use of a Dictionary in Conjunction with a Handwritten Texts Recognizer,
ICPR86(699-701). BibRef 8600

Sagawa, T., Tanaka, E., Suzuki, M., Fujita, M.,
An Unsupervised Learning of Hand-Printed Characters with Linguistic Information,
ICPR84(766-769). BibRef 8400

Kuklinski, T.T.,
Components of Handprint Style Variabilty,
ICPR84(924-926). BibRef 8400

Chapter on OCR, Document Analysis and Character Recognition Systems continues in
Handwritten Characters, Feature Extraction .

Last update:Apr 12, 2014 at 21:44:02