Writer identification forensic system based on support vector machines with connected components

Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science)

Volumn 3029, Issue , 2004, Pages 625-632

  Tapiador, Marino ^a   Gómez, Jaime ^a   Sigüenza, Juan A ^a  

^a UNIVERSIDAD AUTÓNOMA DE MADRID   (Spain)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; COMPUTER SUPPORTED COOPERATIVE WORK; DATA ACQUISITION; DATABASE SYSTEMS; FEATURE EXTRACTION; IMAGE SEGMENTATION; INFORMATION RETRIEVAL SYSTEMS; PROBLEM SOLVING; EXPERT SYSTEMS; SUPPORT VECTOR MACHINES;

BIOMETRIC DATA; FORENSIC SYSTEMS; SUPPORT VECTOR MACHINES (SMV); TOPOGRAPHICAL ANALYSIS; CHARACTER LEVEL; CHARACTER SEGMENTATION; CONNECTED COMPONENT; GRADIENT VECTORS; HUMAN SUPPORT; REAL-LIFE DATABASE; WRITER IDENTIFICATION;

IDENTIFICATION (CONTROL SYSTEMS); ARTIFICIAL INTELLIGENCE;

EID: 9444271024     PISSN: 03029743     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1007/978-3-540-24677-0_64     Document Type: Conference Paper

References (17)

1. H. Hardy and W. Fagel, "Methodological aspects of handwriting identification," Journal of Forensic Document Examination, Fall, 1995.
2. R. A. Huber and A. M. Headrick, Handwriting identification: facts and fundamentals. Ed. CRC Press, 1999.
3. A. K. Jain, R. Bolle, and S. Pankanti, Biometrics. Personal identification in networked society. Ed. Kluwer Academic Publishers, 1999.
4. D. D. Zhang, Automated biometrics. Technologies and systems. Ed. Kluwer Academic Publishers, 2000.
5. S. N. Srihari et al., "Handwriting identification: research to study validity of individuality of handwriting and develop computer-assisted procedures for comparing handwriting," Tech. Rep. CEDAR-TR-01-1, Center of Excellence for Document Analysis and Recognition, University at Buffalo, State University of New York, Feb. 2001, 54 pp.
6. th. British Machine Vision Conference, 2000, pp. 478-487.
7. W. Kuckuck, "Writer recognition by spectra analysis," in Proc. Int. Conf. In Security Through Science Engineering, 1980, West Berlin, Germany, pp. 1-3.
8. th. Int. Conf. on Document Analysis and Recognition (ICDAR'01), Seattle, WA, Sep. 2001, pp. 106-109.
9. th Int. Workshop on Frontiers of Handwriting Recognition (IWFHR2000), Amsterdam, The Netherlands, Sep. 2000, pp. 333-342.
10. th. Int. Conf. on Document Analysis and Recognition (ICDAR'03), Edinburgh, Scotland, Aug. 2003, paper id 527.
11. S. Impedovo, Fundamentals in Handwriting Recognition, Ed. Berlin Heidelberg: Springer-Verlag, 1994.
12. R. C. Gonzalez, R. E. Woods, Digital Image Processing. Ed. Addison-Wesley, 1992.
13. N. Otsu, "A threshold selection method from gray-scale histogram," IEEE Transactions System, Man and Cybernetics, vol. 9, pp. 62-66, Jan. 1979.
14. R. N. Morris, "Forensic Handwriting Identification:fundamental concepts and principles". Ed. Academic Press, 2000.
15. V. Vapnik. 'The Nature of Statistical Learning Theory". Springer-Verlag, New York, 1995.
16. C. Burges and B. Schölkopf. "Improving the accuracy and speed of support vector learning machines". In M. Mozer, M. Jordan, and T. Petsche, editors, Advances in Neural Information Processing Systems 9, pp 375-381, Cambridge, MA, 1997. MIT Press.
17. C. Burges. "A Tutorial on Support Vector Machines for Pattern Recognition". Knowledge Discovery and Data Mining, 2(2), pp 121-167, 1998.