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Clustering and classifying images with local and global variability

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  • Peña Sánchez de Rivera, Daniel
  • Lillo Rodríguez, Rosa Elvira
  • Giuliodori, Andrea

Abstract

A procedure for clustering and classifying images determined by three classification variables is presented. A measure of global variability based on the singular value decomposition of the image matrices, and two average measures of local variability based on spatial correlation and spatial changes. The performance of the procedure is compared using three different databases.

Suggested Citation

  • Peña Sánchez de Rivera, Daniel & Lillo Rodríguez, Rosa Elvira & Giuliodori, Andrea, 2009. "Clustering and classifying images with local and global variability," DES - Working Papers. Statistics and Econometrics. WS ws090101, Universidad Carlos III de Madrid. Departamento de Estadística.
  • Handle: RePEc:cte:wsrepe:ws090101
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    File URL: https://e-archivo.uc3m.es/bitstream/handle/10016/3419/ws090101.pdf?sequence=1
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    References listed on IDEAS

    as
    1. Marron, J.S. & Todd, Michael J. & Ahn, Jeongyoun, 2007. "Distance-Weighted Discrimination," Journal of the American Statistical Association, American Statistical Association, vol. 102, pages 1267-1271, December.
    2. Peña, Daniel & Rodríguez, Julio, 2003. "Descriptive measures of multivariate scatter and linear dependence," Journal of Multivariate Analysis, Elsevier, vol. 85(2), pages 361-374, May.
    3. Benito, Mónica & Peña, Daniel, 2004. "Dimensionality reduction with image data," DES - Working Papers. Statistics and Econometrics. WS ws041003, Universidad Carlos III de Madrid. Departamento de Estadística.
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    Keywords

    Classification;

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