EFFICIENT IMAGE REDUCTION FOR FAST INTELLIGIBLE CLASSIFICATION

Marc Joliveau

Abstract

In the past decades, many domains collected great amounts of data, particularly multimedia files, and stored them in large databases. Therefore, area such as similarity search for image learning have received much attention in the recent years. This paper presents an innovative way to strongly reduce dimension and keep relations between components of an image data set. Our method is validated on the Mnist learning database containing 70000 pictures of handwritten digits. Results demonstrate that the proposed approach is very efficient. It allows to accurately classify, learn, and identify digits using very short computation time in comparison with those obtained with original full-size images.

References

  1. Bauzer-Medeiros, C., Joliveau, M., Jomier, G., and DeVuyst, F. (2008). Managing sensor data on urban traffic. Advances in Conceptual Modeling - Challenges and Opportunities, 5232/2008:385-394.
  2. Bauzer-Medeiros, C., Joliveau, M., Jomier, G., and DeVuyst, F. (2009). Managing sensor traffic data and forecasting unusual behaviour propagation. Geoinformatica.
  3. Joliveau, M. (2008). Reduction of urban traffic time series from georeferenced sensors, and extraction of spatiotemporal series. PhD thesis, Ecole Centrale Des Arts Et Manufactures (Ecole Centrale Paris).
  4. Joliveau, M. and DeVuyst, F. (2007). Space-time summarization of multisensor time series. case of missing data. In Proc. of 2007 International Workshop on Spatial and Spatio-Temporal Data Mining, pages 631-636.
  5. Joliveau, M. and DeVuyst, F. (2008). Recherche de motifs spatio-temporels de cas atypiques pour le trafic routier urbain. Extraction et Gestion de Connaissances EGC 08, Revue des Nouvelles Technologies de l'Information - RNTI - E11, F. Guillet et B. Trousse, 2:523-534.
  6. Jolliffe, I. (1986). Principal component analysis. SpringerVerlag, New York.
  7. Keysers, D., Deselaers, T., Gollan, C., and Ney, H. (2007). Deformation Models for Image Recognition. IEEE Transactions on Pattern Analysis and Machine Intelligence, 29(8):1422-1435.
  8. Kruskal, J. B. and Wish, M. (1978). Multidimensional Scaling. Sage Publications.
  9. Labusch, K., Barth, E., and Martinetz, T. (2008). Simple method for high-performance digit recognition based on sparse coding. IEEE transactions on neural networks, 19:1885-1889.
  10. Lauer, F., Suen, C., and Bloch, G. (2007). A trainable feature extractor for handwritten digit recognition. Pattern Recognition, 40:1816-1824.
  11. LeCun, Y., Bottou, L., Bengio, Y., and Haffner, P. (1998). Gradient-based learning applied to document recognition. In Proc. of the IEEE, volume 86, pages 2278- 2324.
  12. Ranzato, M., Poultney, C., Chopra, S., and LeCun, Y. (2006). Efficient learning of sparse representations with an energy-based model. In Proc. of Advances in Neural Information Processing System NIPS 2006.
  13. Roweis, T. and Saul, L. (2000). Nonlinear dimensionality reduction by locally linear embedding. Science, 290:2323-2326.
  14. Tenenbaum, J., de Silva, V., and Langford, J. (2000). A global geometric framework for nonlinear dimensionality reduction. Science, 290:2319-2323.
Download


Paper Citation


in Harvard Style

Joliveau M. (2010). EFFICIENT IMAGE REDUCTION FOR FAST INTELLIGIBLE CLASSIFICATION . In Proceedings of the 2nd International Conference on Agents and Artificial Intelligence - Volume 1: ICAART, ISBN 978-989-674-021-4, pages 157-162. DOI: 10.5220/0002691801570162


in Bibtex Style

@conference{icaart10,
author={Marc Joliveau},
title={EFFICIENT IMAGE REDUCTION FOR FAST INTELLIGIBLE CLASSIFICATION},
booktitle={Proceedings of the 2nd International Conference on Agents and Artificial Intelligence - Volume 1: ICAART,},
year={2010},
pages={157-162},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0002691801570162},
isbn={978-989-674-021-4},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 2nd International Conference on Agents and Artificial Intelligence - Volume 1: ICAART,
TI - EFFICIENT IMAGE REDUCTION FOR FAST INTELLIGIBLE CLASSIFICATION
SN - 978-989-674-021-4
AU - Joliveau M.
PY - 2010
SP - 157
EP - 162
DO - 10.5220/0002691801570162