Feature extraction using fractal codes

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 1614, Issue , 1999, Pages 483-493

  Schouten, Ben A M ^a   de zeeuw, Paul M ^a  

^a CWI   (Netherlands)

Author keywords

[No Author keywords available]

Indexed keywords

CODES (SYMBOLS); CONTENT BASED RETRIEVAL; EXTRACTION; FEATURE EXTRACTION; FRACTALS; INFORMATION SYSTEMS; INFORMATION USE; TEXTURES;

FRACTAL CODING; FRACTAL IMAGE CODING; GLOBAL CONTRASTS; MULTIMEDIA DATABASE; SIMPLE INFORMATIONS; SPATIAL INFORMATIONS; SPATIAL SIMILARITY; STRUCTURAL CONTENT;

IMAGE CODING;

EID: 22944438686     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/3-540-48762-x_60     Document Type: Conference Paper

References (17)

1. P. Aigrain, H. Zhang, D. Petkovic, Con tent-Based Representation and Retrieval of Visual Media: A State-of-the-Art Review. Multimedia Tools and Applications, 3, pp. 203-223, Kluwer 1996.
2. G. M. Davis, A Wavelet-Based Analysis of Fractal Image Compression. IEEE Transactions on Image Processing, Vol. 7, No. 2, Feb 1998. 484.
3. J.-L. Dugelay, B. Fasel, V. Paoletti, N. Vallet, www. eurecom. fr/-image/Projet Etudiant 1997/english/codeur. html. 484.
4. Y. Fisher (ed.), Fractal Image Compression, Theory and Application, Springer Verlag, 1994. 484, 489.
5. V. N. Gudivada and V. V. Raghavan, Design and evaluation of algorithms for image retrieval by spatial similarity. ACM transactions on Information Systems, Vol. 13, No. 2, p p. 115-144, April 1995. 487.
6. A. Jacquin, A Fractal Theory of Iterated Markov Operators with Applications to Digital Image Coding, Ph D thesis, Georgia Institute of Technology, August 1989. 484.
7. T. Kato, Database architecture for content-based image retrieval. Proc. of SPIE Conf. on Image Storage and Retrieval Systems, Vol. 1662, p p. 112-123, San Jose, Feb 1992. 487.
8. J. M. Keller and S. Chen, Texture description and segmentation through fractal geometry. Computer Vision, Graphics, and Image Processing, 45: 150-166, 1989.
9. J. M. Marie-Julie and H. Essafi, Image Database Indexing and Retrieval Using the Fractal Transform. Proc. of Multimedia Applications, S ervices and Techniques, p p. 169-182, Springer Verlag 1997. 483, 491.
10. W. Niblack, R. Barber, W. Equitz, M. Glasman, D. Petkovic, P. Yanker, C. Faloutsos and G. Taubin, The QBIC Project: querying images by content using color, texture and shape. Storage and Retrieval for Image and Videodatabases 1908, 173-187, 1993. 483, 486, 487.
11. G. E. Oien, R. Hamzaoui and D. Saupe, On the limitations of fractal image texture coding. 487.
12. A. Pentland, R. W. Picard, S. Sclaroff, Photobook: content-based manipulation of image databases. Storage and Retrieval Image and Video Databases II, vol. 2185, SPIE, pp. 34-37. San Jose, 1994. 483, 486, 487.
13. D. Saupe and R. Hamzaoui (eds.), ft p://ftp. informatik. unifreiburg. de/papers/fractal/README. html. 484.
14. Alan D. Sloan, Retrieving Database Contents by Image Recognition: New Fractal Power. Advanced Imaging, 9(5): 26-30, 5 1994. 483, 491.
15. H. Tamura, S. Mori and T. Yamawaki, Texture Features Corresponding to Visual Perception. IEEE Transactions on Systems, Man and Cybernetics, 8(6), June 1978. 483.
16. J. K. Wu and A. D. Narasimhalu, Identifying Faces Using Multiple Retrievals, IEEE Multimedia, 1(2): 27-38, 1994.
17. Aidong Zhang, Biao Cheng, Raj Achary and Raghu Menon, Comparison of Wavelet Transforms and Fractal Coding in Texture-based Image Retrieval. Proceedings of the SPIE Conference on Visual Data Exploration and Analysis III, San Jose, January 1996. 483, 491.