IMAGE CONTENTS ANNOTATIONS WITH THE ENSEMBLE OF ONE-CLASS SUPPORT VECTOR MACHINES

Boguslaw Cyganek, Kazimierz Wiatr

2011

Abstract

The paper presents a system for automatic image indexing based on color information. The main idea is to build a model which represents contents of a reference image in a form of an ensemble of properly trained classifiers. A reference image is first k-means segmented starting from the characteristic colors. Then, each partition is encoded by the one-class SVM. This way an ensemble of classifiers is obtained. During operation, a test image is classified by the ensemble which responds with a measure of similarity between the reference and test images. The experimental results show good performance of image indexing based on their characteristic colors.

References

  1. Aherne, F. J., Thacker, N. A., Rockett, P. I., 1998. The Bhattacharyya Metric as an Absolute Similarity Measure for Frequency Coded Data. Kybernetika, Vol. 34, No. 4, pp. 363-368.
  2. Bertsekas, D. P., 1996. Constraint Optimization and Lagrange Multiplier Methods. Athena Scientific.
  3. Bhattacharyya, A., 1943. On a Measure of Divergence Between Two Statistical Populations Defined by their Probability Distributions. Bull. Calcutta Mathematic Society, Vol. 35, pp. 99-110.
  4. Cyganek, B., Siebert, J. P., 2009. An Introduction to 3D Computer Vision Techniques and Algorithms, Wiley.
  5. Cyganek, B., 2010. Image Segmentation with a Hybrid Ensemble of One-Class Support Vector Machines. HAIS 2010, Part I, Lecture Notes in Artificial Intelligence 6076, Springer, pp. 256-263.
  6. Duda, R. O., Hart, P. E., Stork, D. G., 2001. Pattern Classification. Wiley.
  7. Filippone, M., Camastra, F., Masullia, F., Rovetta, S., 2008. A survey of kernel and spectral methods for clustering. Pattern Recognition 41, pp. 176-190.
  8. Fletcher, R., 2003. Practical Methods of Optimization, 2nd edition. Wiley.
  9. Flickr, 2011. http://www.flickr.com/
  10. Gestel, T. V., Suykens, J. A. K., Baesens, B., Viaene, S., Vanthienen, J., Dedene, G., De Moor, B., Vandewalle, J., 2004. Benchmarking least squares support vector machine classifiers. Machine Learning, Vol. 54, No. 1, pp. 5-32.
  11. Hermes, T., Miene, A., Herzog, O., 2005. Graphical Search for Images by Picture-Finder. Multimedia Tools and Applications. Special Issue on Multimedia Retrieval Algorithmics, Vol. 27, No. 2, pp. 229-250.
  12. Hsu, C-W., Chang, C-C., Lin, C-J., 2003. A Practical Guide to Support Vector Classification. Department of Computer Science and Information Engineering, National Taiwan University, (www.csie.ntu.edu.tw/ cjlin/papers/guide/guide.pdf)
  13. Koen, E. A. van de Sande, Gevers, T., Snoek, C. G. M., 2010. Evaluating Color Descriptors for Object and Scene Recognition. IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 32, No. 9, pp. 1582-1596.
  14. Kruse, R., Döring, C., Lesot, M-J., 2007. Fundamentals of Fuzzy Clustering, in Advances in Fuzzy Clustering and its Applications, ed. de Oliveira, J.,V., Pedrycz, W., Wiley, pp. 3-30.
  15. Kuncheva, L. I., 2004. Combining Pattern Classifiers. Wiley.
  16. Müller, H., Clough, P., Deselaers, T., Caputo, B., 2010. ImageCLEF. Experimental Evaluation in Visual Information Retrieval. Springer.
  17. Schölkopf, B., Smola, A. J., 2002. Learning with Kernels, MIT Press.
  18. Shawe-Taylor, J., Cristianini, N., 2004. Kernel Methods for Pattern Analysis. Cambridge University Press.
  19. Tax, D. M. J., 2001. One-class classification. PhD thesis, TU Delft University.
  20. Tax, D., Duin, R., 2004. Support Vector Data Description, Machine Learning 54, pp.45-66.
  21. Vapnik V. N., 1995. The Nature of Statistical Learning Theory, Springer.
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Paper Citation


in Harvard Style

Cyganek B. and Wiatr K. (2011). IMAGE CONTENTS ANNOTATIONS WITH THE ENSEMBLE OF ONE-CLASS SUPPORT VECTOR MACHINES . In Proceedings of the International Conference on Neural Computation Theory and Applications - Volume 1: NCTA, (IJCCI 2011) ISBN 978-989-8425-84-3, pages 277-282. DOI: 10.5220/0003684002770282


in Bibtex Style

@conference{ncta11,
author={Boguslaw Cyganek and Kazimierz Wiatr},
title={IMAGE CONTENTS ANNOTATIONS WITH THE ENSEMBLE OF ONE-CLASS SUPPORT VECTOR MACHINES},
booktitle={Proceedings of the International Conference on Neural Computation Theory and Applications - Volume 1: NCTA, (IJCCI 2011)},
year={2011},
pages={277-282},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003684002770282},
isbn={978-989-8425-84-3},
}


in EndNote Style

TY - CONF
JO - Proceedings of the International Conference on Neural Computation Theory and Applications - Volume 1: NCTA, (IJCCI 2011)
TI - IMAGE CONTENTS ANNOTATIONS WITH THE ENSEMBLE OF ONE-CLASS SUPPORT VECTOR MACHINES
SN - 978-989-8425-84-3
AU - Cyganek B.
AU - Wiatr K.
PY - 2011
SP - 277
EP - 282
DO - 10.5220/0003684002770282