Symbol descriptor based on shape context and vector model of information retrieval

DAS 2008 - Proceedings of the 8th IAPR International Workshop on Document Analysis Systems

Volumn , Issue , 2008, Pages 191-197

  Nguyen, T O ^a   Tabbone, S ^a   Terrades, O Ramos ^a  

^a LORIA   (France)

Author keywords

[No Author keywords available]

Indexed keywords

ELECTRONIC WARFARE; INFORMATION RETRIEVAL; INTELLIGENT VEHICLE HIGHWAY SYSTEMS; MILITARY ELECTRONIC COUNTERMEASURES; TECHNICAL PRESENTATIONS; VECTORS;

ADAPTIVE METHODS; DESCRIPTOR; GEOMETRIC TRANSFORMS; INTEREST POINTS; SHAPE CONTEXTS; SHAPE DESCRIPTORS; VECTOR MODELS; VISUAL WORDS;

INFORMATION SERVICES;

EID: 57649143445     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/DAS.2008.58     Document Type: Conference Paper

References (21)

1. S. Agarwal, A. Awan, and D. Roth. Learning to detect objects in images via a sparse, part-based representation. IEEE Transactions on Pattern Analysis and Machine Intelligence, 26(11): 1475-1490, November 2004.
2. R. Baeza-Yates and B. Ribeiro-Neto. Modern Information Retrieval. ACM Press / Addison Wesley, New York, 1999.
3. S. Belkasim, M. Shridar, and M. Ahmadi. Pattern recognition with moment invariants: a comparative study and new results. Pattern Recognition, 24:1117-1138, 1991.
4. S. Belongie, J. Malik, and J. Puzicha. Shape matching and object recognition using shape contexts. IEEE Transactions on Pattern Analysis and Machine Intelligence, 24(4):509-522, Avril 2002.
5. A. Bosch, A. Zisserman, and X. Munoz. Scene classification via plsa. In Computer Vision ECCV 2006, volume 3954/2006, pages 517-530. Springer Berlin / Heidelberg, May 2006.
6. A. Jain, R. Duin, and J. Mao. Statistical pattern recognition: a review. IEEE Transactions on Pattern Analysis and Machine Intelligence, 22(1):437, 2000.
7. F. Long, H. Zhang, and D. D. Feng. Multimedia Information Retrieval and Management - Technological Fundamentals and Applications, chapter Fundamentals of Contentbased Image retrieval. Spinger, 2002.
8. D. G. Lowe. Distinctive image features from scale-invariant keypoints. International Journal of Computer Vision, 60(2):91-110, November 2004.
9. S. Marshall. Review of shape coding techniques. Image Vision Computing, 7(4):281-294, 1989.
10. K. Mikolajczyk and C. Schmid. Indexing based on scale invariant interest points. In International Conference on Computer Vision, volume 1, pages 525-531, July 2001.
11. K. Mikolajczyk and C. Schmid. A performance evaluation of local descriptors. IEEE Transactions on Pattern Analysis & Machine Intelligence, 27(10):1615-1630, October 2005.
12. R. Prokop and A. Reeves. A survey of moment-based techniques for unoccluded object representation and recognition. CVGIP: Graphical Models and Image Processing, 54(5):438-460, 1992.
13. Y. Rui, A. She, and T. Huang. A modified fourier descriptor for shape matching in mars. In Workshop on Image Databases and Multi Media Search, volume 8, pages 165-180, 1998.
14. C. Schmid, R. Mohr, and C. Bauckhage. Comparing and evaluating interest points. In In Proceedings of the ICCV, Bombay, India, pages 230-235, 1998.
15. L. Shapiro and G. Stockman. Computer Vision, chapter 8. Content-Based Image Retrieval, pages 249-273. Prentice Hall, 2001.
16. J. Sivic and A. Zisserman. Video google: Efficient visual search of videos. In Toward Category-Level Object Recognition, volume 4170/2006, pages 127-144. Springer Berlin / Heidelberg, 2006.
17. J. R. Smith. Image retrieval evaluation. In IEEE Workshop on Content-based Access to Image and Video Databases, page 112. IEEE Computer Society Washington, DC, USA, June 1998.
18. S. Tabbone, L. Alonso, and D. Ziou. Behavior of the laplacian of gaussian extrema. Journal of Mathematical Imaging and Vision, 23(1):107-128, July 2005.
19. S. Tabbone and L. Wendling. Recognition of symbols in grey level line drawings from an adaptation of the radon transform. In In Proceedings of 17th International Conference on Pattern Recognition, Cambridge (UK), volume 2, pages 570-573, 2004.
20. Th.Gevers and A. Smeulders. Emerging Topics in Computer Vision, chapter 8. Content-Based Image Retrieval: An Overview. Addison-Wesley / Prentice Hall, 2004.
21. D. Zhang and G. Lu. Study and evaluation of different fourier methods for image retrieval. Image and Vision Computing, 23:3349, 2005.