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Clustering and classifying images with local and global variability

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  • Giuliodori, Andrea
  • Lillo Rodríguez, Rosa Elvira
  • Peña, Daniel

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

  • Giuliodori, Andrea & Lillo Rodríguez, Rosa Elvira & Peña, Daniel, 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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    References listed on IDEAS

    as
    1. 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.
    2. 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.
    3. Benito Bonito, 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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