25.4.2 General Character Recognition Issues

Chapter Contents (Back)
OCR. Character Recognition. Some related papers are under Segmentation (especially thresholding, and character segmentation):

Chow, C.K.,
An Optimum Character Recognition System Using Decision Function,
TC(6), No. 4, December 1957, pp. 247-254. Pattern Classification. First introduction of Rejection in the classification problem.
See also On Optimum Recognition Error and Reject Trade-Offs. BibRef 5712

Evey, R.J.,
Use of a Computer to Design Character Recognition Logic,
EJCC59(205-211). BibRef 5900

Bomba, J.S.,
Alpha-Numeric Character Recognition Using Local Operations,
EJCC59(218). BibRef 5900

Highleyman, W.H.,
An Analog Method for Character Recognition,
TC(10), 1961, pp. 502-512. BibRef 6100

Kamentsky, L.A., and Liu, C.N.,
Computer-Automated Design of Multifont Print Recognition,
IBMRD(7), No. 1, 1963, pp. 2-13. N-Tuple matching technique. BibRef 6300

Kamentsky, L.A.,
Pattern and Character Recognition: Picture Processing by Nets of Neuron-Like Elements,
WJCC59(304). BibRef 5900

Kirsch, R.A.,
Computer Interpretation of English Text and Picture Patterns,
TC(13), August 1964, pp. 363-376. BibRef 6408

Edwards, A.W.[A. Wood], and Chambers, R.L.[Robert L.],
Can A Priori Probabilities Help In Character Recognition?,
JACM(11), No. 4, October 1964, pp. 465-470. BibRef 6410

Armitage, J.D., Lohmann, A.W.,
Character Recognition by Incoherent Spatial Filtering,
AppOpt(4), No. 4, April 1965, pp. 461-467. BibRef 6504

vander Lugt, A.B., Rotz, F.B., Klooster, A.,
Character-Reading by Optical Spatial Filtering,
OE-OIP65(xx), 1965. BibRef 6500

Kozlay, D.,
Feature Extraction in an Optical Character Recognition Machine,
TC(20), No. 9, September 1971, pp. 1063. BibRef 7109

Bowman, R.M., McVey, E.S.,
A method for the optimal design of a class of pattern recognition systems,
PR(2), No. 3, September 1970, pp. 187-197.
Elsevier DOI 0309
Allow an equal variance in all portions of a pattern are made on single rows and columns of a two-dimensional binary image of the pattern. OCR. BibRef

Bowman, R.M., McVey, E.S.,
Calculation of multi-category minimum distance classifier recognition error for binomial measurement distributions,
PR(4), No. 3, October 1972, pp. 275-288.
Elsevier DOI 0309
Calculate recognition error for minimum Hamming distance classifiers, a special case of the Bayes (optimum) classifier under certain constraints. BibRef

Ullmann, J.R.,
Picture analysis in character recognition,
DPA76(295-343).
Springer DOI BibRef 7600

Ullmann, J.R.,
Reduction of the storage requirements of Bledsoe and Browning's n-tuple method of pattern recognition,
PR(3), No. 3, October 1971, pp. 297-306.
Elsevier DOI 0309
Random superimposed coding has reduced the massive storage requirements.
See also Pattern Recognition and Reading by Machine. BibRef

Holt, A.W.,
Some Concepts of Character Recognition,
PR(8), No. 2, April 1976, pp. 63-105. Special issue editor. BibRef 7604

Riseman, E.M., Hanson, A.R.,
A Contextual Postprocessing System for Error Correction Using Binary N-Grams,
TC(23), 1974, pp. 480-493. BibRef 7400

Neuhoff, D.L.[David L.],
The Viterbi algorithm as an aid in text recognition,
IT21), March, 1975, pp. 222-226. BibRef 7503

Wendling, S., Gagneux, G.,
Metric invariants for unitary transformations and their application in character recognition,
PR(9), No. 4, 1977, pp. 233-240.
Elsevier DOI 0309
BibRef

Shinghal, R., Toussaint, G.T.,
Experiments in Text Recognition with the Modified Viterbi Algorithm,
PAMI(1), No. 2, April 1979, pp. 184-192. BibRef 7904

Fritzsch, K.,
A matrix approach to character recognition,
PR(11), No. 3, 1979, pp. 165-168.
Elsevier DOI 0309
BibRef

Lai, M.T.Y.[Michael T.Y.], Suen, C.Y.[Ching Y.],
Automatic recognition of characters by Fourier descriptors and boundary line encodings,
PR(14), No. 1-6, 1981, pp. 383-393.
Elsevier DOI 0309
BibRef

Tanaka, H., Hirakawa, Y., Kaneku, S.,
Recognition of Distorted Patterns Using the Viterbi Algorithm,
PAMI(4), No. 1, January 1982, pp. 18-25. BibRef 8201

Wang, Q.R., Suen, C.Y.,
Analysis and Design of a Decision Tree Based on Entropy Reduction and Its Application to Large Character Set Recognition,
PAMI(6), No. 4, July 1984, pp. 406-417. BibRef 8407

Hull, J.J., Srihari, S.N.[Sargur N.],
Experiments in Text Recognition with Binary N-Gram and Viterbi Algorithms,
PAMI(4), No. 5, September 1982, pp. 520-530. BibRef 8209

Hull, J.J., Srihari, S.N., and Choudhari, R.,
An Integrated Algorithm for Text Recognition: Comparison with a Cascaded Algorithm,
PAMI(5), No. 4, July 1983, pp. 384-395. BibRef 8307

Sato, K.[Koji], Isshiki, I.[Isao], Ohoka, A.[Akihiro], Yoshida, K.[Kenichi], Tanaka, K.[Kokichi], Tamura, S.[Shinichi],
Hand-Scan OCR with a One-Dimensional Image Sensor,
PR(16), No. 5, 1983, pp. 459-467.
Elsevier DOI BibRef 8300

Shridhar, M., Badreldin, A.,
High Accuracy Character Recognition Algorithm Using Fourier and Topological Descriptors,
PR(17), No. 5, 1984, pp. 515-524.
Elsevier DOI 0309
BibRef

Casey, R.G., Nagy, G.,
Decision Tree Design Using a Probabilistic Model,
IT(30), 1984, pp. 93-99. BibRef 8400

Stentiford, F.W.M.,
Automatic Feature Design for Optical Character Recognition Using an Evolutionary Search Procedure,
PAMI(7), No. 3, May 1985, pp. 349-355. BibRef 8505

Nagahashi, H., Nakatsuyama, M.,
A Pattern Description and Generation Method of Structural Characters,
PAMI(8), No. 1, January 1986, pp. 112-118. BibRef 8601

Hirota, K., Pedrycz, W.,
Subjective Entropy of Probabilistic Sets and Fuzzy Cluster Analysis,
SMC(16), 1986, pp. 173-179. BibRef 8600

Parthasarathy, G., Chatterji, B.N.,
The Use of Data Windows in Feature Extraction for High Dimensional PR Problems,
PRL(4), 1986, pp. 25-30. BibRef 8600

Baird, H.S.[Henry S.],
Feature Identification for Hybrid Structural/Statistical Pattern Classification,
CVGIP(42), No. 3, June 1988, pp. 318-333.
Elsevier DOI BibRef 8806
Earlier: CVPR86(150-155). BibRef

Winzer, G.[Gerhard],
Character Recognition With a Coherent Optical Multichannel Correlator,
TC(24), No. 4, April 1975, pp. 419-423. BibRef 7504

Ramesh, S.R.,
A generalized character recognition algorithm: A graphical approach,
PR(22), No. 4, 1989, pp. 347-350.
Elsevier DOI 0309
BibRef

Tu, T.Y.[Tsing-Yee], Ma, Y.L.[Yung-Lung],
Character recognition by stochastic sectionalgram approach,
PR(22), No. 5, 1989, pp. 593-601.
Elsevier DOI 0309
BibRef

Tachikawa, M.[Michiyoshi], Ishigami, M.[Masayuki], Ishizaki, H.[Hiroyoshi], Nakayama, H.[Hiroshi],
Character recognition method for recognizing character in an arbitrary rotation position,
US_Patent5,031,225, Jul 9, 1991
WWW Link. BibRef 9107

Nishida, H., and Mori, S.,
Algebraic Description of Curve Structure,
PAMI(14), No. 5, May 1992, pp. 516-533.
IEEE DOI BibRef 9205
And:
An Algebraic Approach to Automatic Construction of Structural Models,
PAMI(15), No. 12, December 1993, pp. 1298-1311.
IEEE DOI Describe curves in terms of convexity, loop and connectivity. BibRef

Nagy, G., Seth, S.C., Einspahr, K.,
Decoding Substitution Ciphers by Means of Word Matching with Application to OCR,
PAMI(9), No. 5, September 1987, pp. 710-715. BibRef 8709

Nagy, G., Seth, S.C., Einspahr, K., Meyer, T.,
Efficient Algorithm to Decode Substitution Ciphers with Application to OCR,
ICPR86(352-355). BibRef 8600

Zhou, J.Y.[Jiang-Ying], Pavlidis, T.[Theo],
Discrimination of Characters by a Multistage Recognition Process,
PR(27), No. 11, November 1994, pp. 1539-1549.
Elsevier DOI Broad character classes, then specific character in the calss. BibRef 9411

Norton-Wayne, L.,
Pattern Analysis for Point-of-Sale Automation,
PRL(6), 1987, pp. 139-143. BibRef 8700

Cash, G.L.[Glenn L.], Hatamian, M.[Mehdi],
Optical Character Recognition by the Method of Moments,
CVGIP(39), No. 3, September 1987, pp. 291-310.
Elsevier DOI Moments. BibRef 8709

Wang, Q.R., Suen, C.Y.,
Large Tree Classifier with Heuristic Search and Global Training,
PAMI(9), No. 1, January 1987, pp. 91-102. BibRef 8701

Tanaka, E., Kojima, Y.,
A High Speed String Correction Method Using a Hierarchical File,
PAMI(9), No. 6, November 1987, pp. 806-815. BibRef 8711

Ohya, J., Shio, A., and Akamatsu, S.,
Recognizing Characters in Scene Images,
PAMI(16), No. 2, February 1994, pp. 214-220.
IEEE DOI BibRef 9402
Earlier:
A Relaxational Extracting Method for Character Recognition in Scene Images,
CVPR88(424-429).
IEEE DOI BibRef

Chianese, A., Cordella, L.P., de Santo, M., and Vento, M.,
Classifying Character Shapes,
VF91(155-164). Matching the shapes based on descriptors. BibRef 9100

Tung, C.H.[Cheng Huang], Lee, H.J.[Hsi-Jian],
Increasing Character-Recognition Accuracy by Detection and Correction of Erroneously Identified Characters,
PR(27), No. 9, September 1994, pp. 1259-1266.
Elsevier DOI BibRef 9409

Flusser, J.[Jan], Suk, T.[Tomas],
Affine Moment Invariants: A New Tool For Character-Recognition,
PRL(15), No. 4, April 1994, pp. 433-436.
See also Pattern Recognition by Affine Moment Invariants. BibRef 9404
Earlier:
Character recognition by affine moment invariants,
CAIP93(572-577).
Springer DOI 9309
BibRef

Suk, T.[Tomas], Flusser, J.[Jan],
Affine moment invariants generated by automated solution of the equations,
ICPR08(1-4).
IEEE DOI 0812
BibRef

Ham, Y.K., Kang, M.S., Chung, H.K., Park, R.H., Park, G.T.,
Recognition of Raised Characters For Automatic Classification of Rubber Tires,
OptEng(34), No. 1, January 1995, pp. 102-109. BibRef 9501

Avi-Itzhak, H.I.[Hadar I.], Diep, T.A.[Thanh A.], Garland, H.T.[Harry T.],
High-Accuracy Optical Character-Recognition Using Neural Networks with Centroid Dithering,
PAMI(17), No. 2, February 1995, pp. 218-224.
IEEE DOI BibRef 9502
And: A2, A1, A3: US_Patent5,475,768, 12/12/1995.
HTML Version. BibRef

Avi-Itzhak, H.I.[Hadar I.],
Method of OCR template enhancement by pixel weighting,
US_Patent5,379,349, Jan 3, 1995
WWW Link. BibRef 9501

Stringa, L.,
A New Set of Constraint-Free Character Recognition Grammars,
PAMI(12), No. 12, December 1990, pp. 1210-1217.
IEEE DOI BibRef 9012

Lee, S.W., Kim, Y.J.,
Direct Extraction of Topographic Features for Gray Scale Character Recognition,
PAMI(17), No. 7, July 1995, pp. 724-728.
IEEE DOI Skeletons. Analysis and recognition from the gray scale image rather than binary images. BibRef 9507

Portegys, T.E.,
A Search Technique For Pattern-Recognition Using Relative Distances,
PAMI(17), No. 9, September 1995, pp. 910-914.
IEEE DOI BibRef 9509

Chen, S.S., Shih, F.Y., Ng, P.A.,
Fuzzy Typographical Analysis for Character Preclassification,
SMC(25), No. 10, October 1995, pp. 1408-1413. BibRef 9510

Cordella, L.P., de Stefano, C., Vento, M.,
A Neural-Network Classifier for OCR Using Structural Descriptions,
MVA(8), No. 5, 1995, pp. 336-342.
Springer DOI BibRef 9500

Cordella, L.P., de Stefano, C., Della Cioppa, A., Marcelli, A.,
A new evolutionary learning model for handwritten character prototyping,
CIAP99(830-835).
IEEE DOI 9909
BibRef

Yagasaki, T.[Toshiaki],
Method and apparatus for pattern recognition,
US_Patent5,524,065, Jun 4, 1996
WWW Link. OCR BibRef 9606

Kudo, M., Mizukami, K., Nakamura, Y., Shimbo, M.,
Realization of Membership Queries in Character-Recognition,
PRL(17), No. 1, January 10 1996, pp. 77-82. BibRef 9601

Hasegawa, A., Shibata, K., Itoh, K., Ichioka, Y., Inamura, K.,
An Adaptive Neural-Network: Application to Character-Recognition on X-Ray-Films,
NeurNet(9), No. 1, January 1996, pp. 121-127. BibRef 9601

Wilson, C.L., Grother, P.J., Barnes, C.S.,
Binary Decision Clustering for Neural-Network-Based Optical Character-Recognition,
PR(29), No. 3, March 1996, pp. 425-437.
Elsevier DOI BibRef 9603

Hu, J.M., Yan, H.,
Automatic Reading of the White Pages in a Telephone Directory,
OptEng(35), No. 11, November 1996, pp. 3150-3158. 9612
BibRef

Srikantan, G.[Geetha], Lam, S.W.[Stephen W.], Srihari, S.N.[Sargur N.],
Gradient-Based Contour Encoding for Character-Recognition,
PR(29), No. 7, July 1996, pp. 1147-1160.
Elsevier DOI 9607
General features of characters. BibRef

Marcelli, A., Likhareva, N., Pavlidis, T.,
Structural Indexing for Character-Recognition,
CVIU(66), No. 3, June 1997, pp. 330-346.
DOI Link 9706
BibRef

Yasuda, M.[Michio], Yamamoto, K.[Kazuhiko], Yamada, H.[Hiromitsu],
Effect of the Perturbed Correlation Method for Optical Character-Recognition,
PR(30), No. 8, August 1997, pp. 1315-1320.
Elsevier DOI 9708
Analyze correlation method. BibRef

Gatos, B., Papamarkos, N., Chamzas, C.,
Using Curvature Features in a Multiclassifier OCR System,
EngAAI(10), No. 2, April 1997, pp. 213-224. 9706
BibRef

Webster, R.G.[Rodney G.], Nakagawa, M.[Masaki],
An Interface Oriented Approach to Character-Recognition Based on a Dynamic Model,
PR(31), No. 2, February 1998, pp. 193-203.
Elsevier DOI 9802
Dynamic template model. BibRef

Barriere, C., Plamondon, R.,
Human Identification of Letters in Mixed-Script Handwriting: An Upper Bound on Recognition Rates,
SMC-B(28), No. 1, February 1998, pp. 78-82.
IEEE Top Reference. 9802
BibRef

Sarker, P.[Prateek], Nagy, G.[George], Zhou, J.Y.[Jiang-Ying], Lopresti, D.P.[Daniel P.],
Spatial Sampling of Printed Patterns,
PAMI(20), No. 3, March 1998, pp. 344-351.
IEEE DOI 9805
Analysis the effect of variations in the grid for scanning documents. BibRef

Lam, L., Ding, J., Suen, C.Y.,
Differentiating Between Oriental and European Scripts by Statistical Features,
PRAI(12), No. 1, February 1998, pp. 63-79. 9806
BibRef

Sasaki, O., Shibahara, A., Suzuki, T.,
Optical Character Recognition with Feature Extraction and Associative Memory Matrix,
OptEng(37), No. 6, June 1998, pp. 1827-1833. 9806
BibRef

Makhoul, J.[John], Schwartz, R.[Richard], La Pre, C.[Christopher], Bazzi, I.[Issam],
A Script Independent Methodology for Optical Character Recognition,
PR(31), No. 9, September 1998, pp. 1285-1294.
Elsevier DOI 9808
BibRef

de Carvalho, A., Fairhurst, M.C.,
Applying Adaptive Logic Networks to Character Recognition,
PRL(19), No. 5-6, April 1998, pp. 469-473. 9808
BibRef

Tan, T.N.,
Rotation Invariant Texture Features and Their Use in Automatic Script Identification,
PAMI(20), No. 7, July 1998, pp. 751-756.
IEEE DOI 9808
Detection of which script is used -- to determine which OCR should be used. Build on texture features. BibRef

Tan, T.N.[Tie-Niu],
Written Language Recognition Based on Texture Analysis,
ICIP96(II: 185-188).
IEEE DOI BibRef 9600

Kim, J.T.[Jung-Tae], Bang, S.Y.[Sung-Yang],
A Measure of Recognition Difficulty for a Character Image Database,
PR(31), No. 12, December 1998, pp. 2001-2006.
Elsevier DOI BibRef 9812
Earlier: A1 only: ICDAR97(996-1000).
IEEE DOI 9708
BibRef

Veeramachaneni, S.[Sriharsha], Nagy, G.[George],
Adaptive classifiers for multisource OCR,
IJDAR(6), No. 3, March 2004, pp. 154-166.
Springer DOI 0406
BibRef

Nagy, G., Xu, Y.,
Automatic Prototype Extraction for Adaptive OCR,
ICDAR97(278-282).
IEEE DOI 9708
BibRef

Wang, X.W.[Xue-Wen], Ding, X.Q.[Xiao-Qing], Liu, C.S.[Chang-Song],
Gabor filters-based feature extraction for character recognition,
PR(38), No. 3, March 2005, pp. 369-379.
Elsevier DOI 0412
BibRef
Earlier:
Optimized gabor filter based feature extraction for character recognition,
ICPR02(IV: 223-226).
IEEE DOI 0211
BibRef

Padma, M.C., Vijaya, P.A.,
Word level identification of Kannada, Hindi and English scripts from a tri-lingual document,
IJCVR(1), No. 2, 2010, pp. 218-235.
DOI Link 1011
BibRef

Visani, M.[Muriel], Terrades, O.R.[Oriol Ramos], Tabbone, S.A.[Salvatore A.],
A protocol to characterize the descriptive power and the complementarity of shape descriptors,
IJDAR(14), No. 1, March 2011, pp. 87-100.
WWW Link. 1103
BibRef

Dhandra, B.V., Mukarambi, G.[Gururaj], Hangarge, M.[Mallikarjun],
A recognition system for handwritten Kannada and English characters,
IJCVR(2), No. 4, 2011, pp. 290-301.
DOI Link 1202
BibRef

Urolagin, S.[Siddhaling], Prema, K.V., Subba Reddy, N.V.,
Kannada Alphabets Recognition With Application To Braille Translation,
IJIG(11), No. 1, January 2011, pp. 293-314.
DOI Link 1108
BibRef

Ryu, S.J.[Sang-Jin], Kim, I.J.[In-Jung],
Discrimination of similar characters using nonlinear normalization based on regional importance measure,
IJDAR(17), No. 1, March 2014, pp. 79-89.
WWW Link. 1403
BibRef

Ait-Mohand, K.[Kamel], Paquet, T.[Thierry], Ragot, N.[Nicolas],
Combining Structure and Parameter Adaptation of HMMs for Printed Text Recognition,
PAMI(36), No. 9, September 2014, pp. 1716-1732.
IEEE DOI 1408
Adaptation models BibRef

Mohand, K.A.[Kamel Ait], Paquet, T.[Thierry], Ragot, N.[Nicolas], Heutte, L.[Laurent],
Structure Adaptation of HMM Applied to OCR,
ICPR10(2877-2880).
IEEE DOI 1008
BibRef

Lagorce, X.[Xavier], Orchard, G.[Garrick], Galluppi, F.[Francesco], Shi, B.E.[Bertram E.], Benosman, R.B.[Ryad B.],
HOTS: A Hierarchy of Event-Based Time-Surfaces for Pattern Recognition,
PAMI(39), No. 7, July 2017, pp. 1346-1359.
IEEE DOI 1706
Biosensors, Cameras, Character recognition, Feature extraction, Object recognition, Visualization, Neuromorphic sensing, event-based vision, feature extraction. BibRef

Sahare, P.[Parul], Dhok, S.B.[Sanjay B.],
Script identification algorithms: a survey,
MultInfoRetr(6), No. 3, September 2017, pp. 211-232.
Springer DOI 1708
Survey, Script. BibRef

Benchaou, S.[Soukaina], Nasri, M.[M'Barek], El Melhaoui, O.[Ouafae],
Feature Selection Based on Evolution Strategy for Character Recognition,
IJIG(18), No. 3, July 2018, pp. Article 1850014.
DOI Link 1807
BibRef

Soukaina, B., Nasri, M., Aouinti, F., Zinedine, K., El Melhaoui, O.,
Optimization of the Attribute Vector by Genetic Approach: Application to the Classification of Characters,
CGiV16(405-409)
IEEE DOI 1608
character recognition BibRef

Ding, H.S.[Hai-Song], Chen, K.[Kai], Huo, Q.A.[Qi-Ang],
Compressing CNN-DBLSTM models for OCR with teacher-student learning and Tucker decomposition,
PR(96), 2019, pp. 106957.
Elsevier DOI 1909
Optical character recognition, CNN-DBLSTM Character model, Model compression, Teacher-student learning, Tucker decomposition BibRef

Parashivamurthy, R.[Ravi], Naveena, C.[Chikkaguddaiah], Kumar, Y.H.S.[Yeliyur Hanumathiah Sharath],
SIFT and HOG features for the retrieval of ancient Kannada epigraphs,
IET-IPR(14), No. 17, 24 December 2020, pp. 4657-4662.
DOI Link 2104
BibRef

Guptha, N.S.[Nirmala S], Balamurugan, V., Megharaj, G.[Geetha], Sattar, K.N.A.[Khalid Nazim Abdul], Rose, J.D.[J. Dhiviya],
Cross lingual handwritten character recognition using long short term memory network with aid of elephant herding optimization algorithm,
PRL(159), 2022, pp. 16-22.
Elsevier DOI 2206
Enhanced local binary pattern, Gaussian filter, Inverse difference moment normalized, Projection profile technique BibRef


Da, C.[Cheng], Wang, P.[Peng], Yao, C.[Cong],
Levenshtein OCR,
ECCV22(XXVIII:322-338).
Springer DOI 2211
BibRef

Reeves, S.I.[Steven I.], Lee, D.W.[Dong-Wook], Singh, A.[Anurag], Verma, K.[Kunal],
A Gaussian Process Upsampling Model for Improvements in Optical Character Recognition,
ISVC20(II:263-274).
Springer DOI 2103
BibRef

Yousef, M., Bishop, T.E.,
OrigamiNet: Weakly-Supervised, Segmentation-Free, One-Step, Full Page Text Recognition by learning to unfold,
CVPR20(14698-14707)
IEEE DOI 2008
Image segmentation, Text recognition, Training, Image recognition, Task analysis BibRef

Zhao, H., Hu, Y., Zhang, J.,
Character Recognition via a Compact Convolutional Neural Network,
DICTA17(1-6)
IEEE DOI 1804
document image processing, feature extraction, learning (artificial intelligence), natural scenes, neural nets, Optical character recognition software BibRef

Peixoto, S.[Sirlene], Gonçalves, G.[Gabriel], Bianchi, A.[Andrea], Brito, A.D.[Alceu De_S.], Schwartz, W.R.[William Robson], Menotti, D.[David],
Noisy Character Recognition Using Deep Convolutional Neural Networks,
CIARP17(499-507).
Springer DOI 1802
BibRef

Tripathy, N., Chakraborti, T., Nasipuri, M., Pal, U.,
A scale and rotation invariant scheme for multi-oriented Character Recognition,
ICPR16(4041-4046)
IEEE DOI 1705
Character recognition, Clustering algorithms, Optical character recognition software, Principal component analysis, Support vector machines, Text recognition, Indic script, Optical Character Recognition (OCR), Principal Component Analysis (PCA), Rotation-invariant scale-invariant features, Support, Vector, Machine, (SVM) BibRef

Stearns, L.[Lee], Du, R.F.[Ruo-Fei], Oh, U.[Uran], Wang, Y.M.[Yu-Meng], Findlater, L.[Leah], Chellappa, R.[Rama], Froehlich, J.E.[Jon E.],
The Design and Preliminary Evaluation of a Finger-Mounted Camera and Feedback System to Enable Reading of Printed Text for the Blind,
ACVR14(615-631).
Springer DOI 1504
BibRef

Hollaus, F.[Fabian], Diem, M.[Markus], Sablatnig, R.[Robert],
Improving OCR Accuracy by Applying Enhancement Techniques on Multispectral Images,
ICPR14(3080-3085)
IEEE DOI 1412
Accuracy BibRef

Jin, X.J.[Xiao-Jie], Wang, Q.F.[Qiu-Feng], Hou, X.W.[Xin-Wen], Liu, C.L.[Cheng-Lin],
Visual Gesture Character String Recognition by Classification-Based Segmentation with Stroke Deletion,
ACPR13(120-124)
IEEE DOI 1408
geometry BibRef

Miyoshi, T., Nagasaki, T., Shinjo, H.,
Moment-Based Character-Normalization Methods Using a Contour Image Combined with an Original Image,
ICDAR13(1066-1070)
IEEE DOI 1312
feature extraction BibRef

Kozielski, M.[Michal], Forster, J.[Jens], Ney, H.[Hermann],
Moment-Based Image Normalization for Handwritten Text Recognition,
FHR12(256-261).
IEEE DOI 1302
BibRef

Pesch, H.[Hendrik], Hamdani, M.[Mahdi], Forster, J.[Jens], Ney, H.[Hermann],
Analysis of Preprocessing Techniques for Latin Handwriting Recognition,
FHR12(280-284).
IEEE DOI 1302
BibRef

Nina, O.A.[Oliver A.],
Interactive Enhancement of Handwritten Text through Multi-resolution Gaussian,
FHR12(769-773).
IEEE DOI 1302
BibRef

Jain, R., Chaudhury, S.,
Probabilistic Approach for Correction of Optically-Character-Recognized Strings Using Suffix Tree,
NCVPRIPG11(74-77).
IEEE DOI 1205
BibRef

Lund, W.B.[William B.], Walker, D.D.[Daniel D.], Ringger, E.K.[Eric K.],
Progressive Alignment and Discriminative Error Correction for Multiple OCR Engines,
ICDAR11(764-768).
IEEE DOI 1111
BibRef

Lund, W.B.[William B.], Ringger, E.K.[Eric K.],
Error Correction with In-domain Training across Multiple OCR System Outputs,
ICDAR11(658-662).
IEEE DOI 1111
BibRef

Perez-Cortes, J.C.[Juan-Carlos], Llobet, R.[Rafael], Navarro-Cerdan, J.R.[Jose-Ramon], Arlandis, J.[Joaquim],
Using Field Interdependence to Improve Correction Performance in a Transducer-Based OCR Post-Processing System,
FHR10(605-610).
IEEE DOI 1011
BibRef
And: A3, A4, A1, A2:
User-Defined Expected Error Rate in OCR Postprocessing by Means of Automatic Threshold Estimation,
FHR10(405-409).
IEEE DOI 1011
BibRef
And: A2, A3, A1, A4:
OCR Post-processing Using Weighted Finite-State Transducers,
ICPR10(2021-2024).
IEEE DOI 1008
BibRef

Wang, N.[Ning], Lam, L.[Louisa], Suen, C.Y.[Ching Y.],
Noise Tolerant Script Identification of Printed Oriental and English Documents Using a Downgraded Pixel Density Feature,
ICPR10(2037-2040).
IEEE DOI 1008
BibRef

Kae, A.[Andrew], Huang, G.B.[Gary B.], Doersch, C.[Carl], Learned-Miller, E.G.[Erik G.],
Improving state-of-the-art OCR through high-precision document-specific modeling,
CVPR10(1935-1942).
IEEE DOI 1006
BibRef

Bakar, N.A.[Norsharina Abu], Shamsuddin, S.M.[Siti Mariyam],
United Zernike Invariants for Character Images,
IVIC09(498-509).
Springer DOI 0911
BibRef

Ko, M.A.[Mi-Ae], Kim, Y.M.[Young-Mo],
A simple OCR method from strong perspective view,
AIPR04(235-240).
IEEE DOI 0410
BibRef

Abdul Kader, A.[Ahmad], Casey, M.R.[Mathew R.],
Low Cost Correction of OCR Errors Using Learning in a Multi-Engine Environment,
ICDAR09(576-580).
IEEE DOI 0907
BibRef

Bhuiyan, M.A.[Mohammad A.], Jalasutram, R.[Rommel], Taha, T.M.[Tarek M.],
Character recognition with two spiking neural network models on multicore architectures,
CIMSVP09(29-34).
IEEE DOI 0903
BibRef

Kuhl, A.[Annika], Tan, T.[Tele], Venkatesh, S.[Svetha],
Model-based combined tracking and resolution enhancement,
ICPR08(1-4).
IEEE DOI 0812
BibRef
And:
Model-based character recognition in low resolution,
ICIP08(1001-1004).
IEEE DOI 0810
5 pixel text. BibRef

Fujisawa, H.[Hiromichi],
How to Deal with Uncertainty and Variability: Experience and Solutions,
SACH06(xx-yy).
Springer DOI 0609
BibRef

Breuel, T.,
The hOCR Microformat for OCR Workflow and Results,
ICDAR07(1063-1067).
IEEE DOI 0709
BibRef

Garain, U.[Utpal], Chakraborty, M.P., Majumder, D.D.[D. Dutta],
Improvement of OCR Accuracy by Similar Character Pair Discrimination: an Approach based on Artificial Immune System,
ICPR06(II: 1046-1049).
IEEE DOI 0609
BibRef

Alon, J., Athitsos, V., Sclaroff, S.,
Online and offline character recognition using alignment to prototypes,
ICDAR05(II: 839-843).
IEEE DOI 0508
BibRef

Chellapilla, K., Simard, P.Y., Nickolov, R.,
Fast optical character recognition through glyph hashing for document conversion,
ICDAR05(II: 829-833).
IEEE DOI 0508
BibRef

Moussa, S.B., Zahour, A.[Abderrazak], Alimi, M.A., Benabdelhafid, A.,
Can fractal dimension be used in font classification,
ICDAR05(I: 146-150).
IEEE DOI 0508
BibRef

Sarkar, P., Baird, H.S.,
Decoder Banks: Versatility, Automation, and High Accuracy without Supervised Training,
ICPR04(II: 646-649).
IEEE DOI 0409
BibRef

Oliveira, A.L.I., Neto, F.B.L., Meira, S.R.L.,
Improving RBF-DDA performance on optical character recognition through parameter selection,
ICPR04(IV: 625-628).
IEEE DOI 0409
BibRef

Seni, G.,
TreadMill ink: Enabling continuous pen input on small devices,
FHR02(215-220).
IEEE Top Reference. 0209
BibRef

Elliman, D., Sherkat, N.,
A truthing tool for generating a database of cursive words,
ICDAR01(1255-1262).
IEEE DOI 0109
BibRef

Da, L.[Lu], McCane, B., Wei, P.[Pu],
Character pre-classification based on fuzzy typographical analysis,
ICDAR01(74-78).
IEEE DOI 0109
BibRef

Kim, H.Y., Kim, J.H.,
Minimum Entropy Estimation of Hierarchical Random Graph Parameters for Character Recognition,
ICPR00(Vol II: 1050-1053).
IEEE DOI 0009
BibRef

Sawaki, M., Murase, H., Hagita, N.,
Automatic Acquisition of Context-based Image Templates for Degraded Character Recognition in Scene Images,
ICPR00(Vol IV: 15-18).
IEEE DOI 0009
BibRef

Murase, H.[Hiroshi], Hagita, N.[Norihiro], Sawaki, M.[Minako],
Character Recognition in Bookshelf Images by Automatic Template Selection,
ICPR98(Vol II: 1117-1120).
IEEE DOI 9808
BibRef

Berthilsson, R.,
Character Recognition Using Shape for Curves,
ICPR00(Vol II: 227-230).
IEEE DOI 0009
BibRef

Wang, X., Ding, X., Liu, C.,
Gray-scale Character Image Recognition Based on Fuzzy DCT Transform Features,
ICPR00(Vol II: 235-238).
IEEE DOI 0009
BibRef

Yoshimura, H., Etoh, M., Kondo, K., Yokoya, N.,
Gray-scale Character Recognition by Gabor Jets Projection,
ICPR00(Vol II: 335-338).
IEEE DOI 0009
BibRef

Baird, H.S., Nagy, G.,
A Self-Correcting 100-Font Classifier,
SPIE(2181), 1994, pp. 106-115. Font specific error rates can clearly be lower. BibRef 9400

Szmurlo, M.,
Boundary Normalization for Recognition of Non-Touching Non-Degraded Characters,
ICDAR97(463-466).
IEEE DOI 9708
BibRef

Sawa, K., Tsuruoka, S., Wakabayashi, T., Kimura, F., Miyake, Y.,
Low Quality String Recognition For Factory Automation,
ICDAR97(475-478).
IEEE DOI 9708
BibRef

Nagasaki, T., Yamamoto, T., Nakagawa, M.,
The Behavior of Dynamic Relaxation in an Elastic Stroke Model for Character Recognition,
ICDAR97(16-22).
IEEE DOI 9708
BibRef

Le Bourgeois, F.,
Robust Multifont OCR System from Gray Level Images,
ICDAR97(1-5).
IEEE DOI 9708
BibRef

Bottou, L.[Leon], Bengio, Y.[Yoshua], Le Cun, Y.L.[Yann L.],
Global Training of Document Processing Systems Using Graph Transformer Networks,
CVPR97(489-494).
IEEE DOI 9704
Learning document analysis. Character recognition. BibRef

Kim, M., Kwon, Y.,
Multi-Font and Multi-Size Character Recognition Based on the Sampling and Quantization of an Unwrapped Contour,
ICPR96(III: 170-174).
IEEE DOI 9608
(Chung-Ang Univ., KOR) BibRef

Takasu, A., Satoh, S., Katsura, E.,
A document understanding method for database construction of an electronic library,
ICPR94(B:463-466).
IEEE DOI 9410
BibRef

Takasu, A., Katayama, N., Yamaoka, M., Iwaki, O., Oyama, K., Adachi, J.,
Approximate Matching for OCR-Processed Bibliographic Data,
ICPR96(III: 175-179).
IEEE DOI 9608
(NACSIS, J) BibRef

Grother, P.J.,
Cross Validation Comparison of NIST OCR Databases,
SPIE(1906), February 1993. BibRef 9302
And: NISTIR5123, January 1992. BibRef

Garris, M.D., Wilson, C.L., Blue, J.L., Candela, G.T., Grother, P.J., Janet, S.A., and Wilkinson, R.A.,
Massively Parallel Implementation of Character Recognition Systems,
SPIE(1661), February 1992, pp. 269-280. BibRef 9202
And: NISTIR4750 January 1992. BibRef

Le Bourgeois, F., and Henry, J.L.,
An Evolutive OCR System Based on Continuous Learning,
WACV96(272-277).
IEEE DOI 9609
BibRef

Ma, Y.L., Jang, S.Y., Ma, C.,
Pattern Recognition by Circular Layer Code Approach,
ICPR86(783-785). BibRef 8600

Kurosawa, Y., Asada, H.,
Attributed String Matching with Statistical Constraints for Character Recognition,
ICPR86(1063-1067). BibRef 8600

Ikeuchi, K.,
A Model of Character Recognition by Humans,
ICPR84(521-524). BibRef 8400

Lu, P.Y., Brodersen, R.W.,
Real-Time On-Line Symbol Recognition Using a DTW Processor,
ICPR84(1281-1283). BibRef 8400

Schuermann, J.[Juergen],
Text Recognition: From Pixels to Meaning,
SDAIR96(XX) Daimler Benz Research Center. BibRef 9600

Drucker, H.[Harris],
Fast Decision Tree Ensembles for Optical Character Recognition,
SDAIR96(XX) AT&T Bell Laboratories. BibRef 9600

Singhal, A.[Amit], Salton, G.[Gerard], Buckley, C.[Chris],
Length Normalization in Degraded Text Collections,
SDAIR96(XX) Cornell University. BibRef 9600

Nagy, G.[George], Wang, X.Y.[Xiao-Yin],
Automatically-Generated High-Reliability Features for Dichotomies of Printed Characters,
SDAIR96(XX) Rensselaer Polytechnic Institute. BibRef 9600

Jager, T.[Thorsten],
OCR and Voting Shell Fulfilling Specific Text Analysis Requirements,
SDAIR96(XX) German Research Center for Artificial Intelligence (DFKI). BibRef 9600

O'Regan, K., Bismuth, N., Hersch, R.D., Pappas, A.,
Legibility of perceptually-tuned grayscale fonts,
ICIP96(I: 537-540).
IEEE DOI 9610
BibRef

Romero, R.D., Tibadeau, R.H.,
Object manipulation for document conversion,
ICIP95(III: 300-303).
IEEE DOI 9510
BibRef

Shchepin, E.V., Nepomnyashchii, G.M.,
On the method of critical points in character recognition,
CAIP93(594-598).
Springer DOI 9309
BibRef

Ong, P.W., Wallace, R.S., Schwartz, E.L.,
Space-variant optical character recognition,
ICPR92(II:504-507).
IEEE DOI 9208
BibRef

Chapter on OCR, Document Analysis and Character Recognition Systems continues in
OCR Systems, General .


Last update:Mar 16, 2024 at 20:36:19