Establishing Handwriting individuality using pattern recognition techniques

Proceedings of the International Conference on Document Analysis and Recognition, ICDAR

Volumn 2001-January, Issue , 2001, Pages 1195-1204

  Srihari, Sargur N ^a   Cha, Sung Hyuk ^a   Lee, Sangjik ^a  

^a UNIVERSITY AT BUFFALO   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; ARTIFICIAL INTELLIGENCE; LEARNING SYSTEMS; PATTERN RECOGNITION;

DEGREE OF CONFIDENCE; ETHNIC GROUPS; EXPERT TESTIMONY; EXTRACTING FEATURES; MACHINE LEARNING APPROACHES; MATHEMATICAL APPROACH; PATTERN RECOGNITION TECHNIQUES; SCANNED IMAGES;

CHARACTER RECOGNITION;

EID: 33745580057     PISSN: 15205363     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICDAR.2001.953974     Document Type: Conference Paper

References (20)

1. Daubert. Daubert vs. merrell dow pharmaceuticals. 509 U.S. 579, 1993.
2. R. O. Duda and P. E. Hart. Pattern classification and scene analysis. New York, John Wiley & Sons, 1973.
3. J. T. Favata, G. Srikantan, and S. N. Srihari. Handprinted character/digit recognition using a multiple feature/resolution philosophy. In IWFHR-IV, pages 57-66, December 1994.
4. H. Freeman. Techniques for the digital computer analysis of chain encoded arbitrary plane curves. In Proc, Nat, Electronics, Conf., Volume 17, pages 412-432, 1961.
5. A. N. Gilbert and C. J. Wysocki. Hand preference and age in the united states. Neuropsychologia, 30(7):601-608, 1992. check the year and get the full names.
6. R. C. Gonzalez and R. E. Woods. Digital Image Processing. Addison-Wesley, 3rd edition, 1992.
7. V. Govindaraju, A. Shekhawat, and S. N. Srihari. Interpretation of handwritten addresses in us mail stream. In 2nd Int. Conf. on Document Analysis and Recognition, pages 291-294, 1993.
8. R. A. Huber and A. M. Headrick. Handwriting Identification: Facts and Fundamentals. CRC Press LLC, 1999.
9. G. Kim and V. Govindaraju. A lexicon driven approach to handwritten word recognition for real-time applications. Transactions on Pattern Analysis and Machine Intelligence, 19(4):366-379, April 1997.
10. D. S. Lee, S. N. Srihari, and R. Gaborski. Bayesian and neural network pattern recognitaion: a theoretical connection and empirical results with handwritten characters. In A. K. J. I. K. Sethi; editor, Artificial Neural Networks and Statistical Pattern Recognition, pages 89-105. Noth-Holland, 1991.
11. S. L. Lohr. Sampling: Design and Analysis. Duxbury Press, Pacific Grove, CA, 1999.
12. B. Mirkin. Mathematical Classification and Clustering. Kluwer Academic Publishers, 1996.
13. T. M Mitchell. Machine Learning. McGraw-Hill, 1997.
14. A. S. Osborn. Questioned Document. Albany, N.Y.: Boyd Print. Co., 2nd edition, 1929.
15. N. Otsu. A threshold selection method from gray-scale histogramz. IEEE Transactions System, Man and Cybernetics, 9:62-66, 1979.
16. S. N. Srihari. Feature extraction for locating address blocks on mail pieces. In J. C. Simon, editor, From Pixels to Features, pages 22-27, August 1988.
17. S. N. Srihari. Recognition of handwritten and machine-printed text for postal address interpretation. Pattern Recognition Letters, 14(4):291-303, 1993.
18. S. N. Srihari, S.-H. Cha, H. Arora, and S. Lee. Handwriting identification: Research to study validity of individuality of handwriting & develop computer-assisted procedures for comparing handwriting. Technical Report CEDAR-TR-01-1, SUNY at Buffalo, March 2001.
19. G. Srikantan, S. W. Lam, and S. N. Srihari. Gradient-based contour encoding for character recognition. Pattern Recognition, 29(7): 1147-1160, 1996.
20. G. Srikantan, D. S. Lee, and J. T. Favata. Comparison of normalization methods for character recognition. In 3rd International Conference on Document Analysis and Recognition, Volume 2, pages 719-722, August 1995.