Learning similarity for texture image retrieval

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

Volumn 1842, Issue , 2000, Pages 178-190

  Guo, Guodong ^a   Li, Stan Z ^a   Chan, Kap Luk ^a  

^a NANYANG TECHNOLOGICAL UNIVERSITY   (Singapore)

Author keywords

Boundary distance metric; Image indexing; Learning pattern similarity; Support vector machines

Indexed keywords

COMPUTER VISION; IMAGE RETRIEVAL; LEARNING ALGORITHMS; QUERY PROCESSING; SUPPORT VECTOR MACHINES; TEXTURES;

DISTANCE METRICS; EUCLIDEAN DISTANCE; IMAGE INDEXING; LEARNING PATTERNS; LEARNING SIMILARITY; PATTERN SIMILARITY; STATISTICAL LEARNING; TEXTURE IMAGE RETRIEVAL;

IMAGE TEXTURE;

EID: 23044518630     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/3-540-45054-8_12     Document Type: Conference Paper

References (16)

1. P. Brodatz, Textures: A Photographic Album for Artists & Designers. New York: Dover, 1966.
2. C. Cortes and V. Vapnik, Support vector networks, Machine Learning, 20, 273-297, 1995.
3. J. G. Daugman, Complete discrete 2-D Gabor transforms by neural networks for image analysis and compression, IEE Trans. ASSP, vol 36, 1169-1179, July 1988.
4. S. Gunn, M. Brown and K. M. Bossley, Network performance assessment for neu-rofuzzy data modeling. Lecture Notes in Computer Science, 1280: 313-323, 1997.
5. S. Gunn, Support vector machines for classification and regression, ISIS Technical Report, May, 1998.
6. W. Y. Ma, NETRA: A Toolbox for Navigating Large Image Databases. PhD thesis, University of California at Santa Barbara, 1997.
7. W. Y. Ma and B. S. Manjunath, Texture features and learning similarity. Proc. CVPR, 425-430, 1996.
8. B. S. Manjunath and W. Y. Ma, Texture features for browsing and retrieval of image data. IEEE PAMI, vol. 18, No, 8, 837-842, 1996.
9. T. P. Minka and R. W. Picard, Interactive learning using a “society of models", Technical Report No. 349, MIT Media Laboratory, 1995.
10. W. Niblack, et al, The QBIC project: querying images by content using color, texture, and shape, Proc. of SPIE, Storage and Retrieval for Image and Video Databases-II, vol. 1908, San Jose, CA, 173-187, Feb. 1993.
11. E. Osuna, R. Freund and F. girosi, Training support vector machines: an application to face detection. Proc. CVPR, 1997.
12. A. Pentland, R. W. Picard, and S. Sclaro_, Photobook: tools for content based manipulation of image databases, Proc. of SPIE, Storage and Retrieval for Image and Video Databases-II, No. 2185, San Jose, CA, 34-47, Feb. 1994.
13. M. Pontil and A. Verri, Support vector machines for 3-D object recognition, IEEE Trans. on Pattern Analysis and Machine Intelligence, vol. 20, 637-646, 1998.
14. J. Buzicha, J. M. Buhmann, Y. Rubner and C. Tomasi, Emperical evaluation of dissimilarity measures for color and texture, Proc. ICCV, vol. II, 1165-1172, 1999.
15. S. Santini and R. Jain, Similarity measures, IEEE Trans. on Pattern Analysis and Machine Intelligence, vol. 21, No. 9, 871-883, 1999.
16. V. N. Vapnik, Statistical learning theory, John Wiley & Sons, New York, 1998