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Clustering and classifying images with local and global variability

Listed author(s):
  • Peña Sánchez de Rivera, Daniel
  • Lillo Rodríguez, Rosa Elvira
  • Giuliodori, Andrea
Registered author(s):

    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.

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    Paper provided by Universidad Carlos III de Madrid. Departamento de Estadística in its series DES - Working Papers. Statistics and Econometrics. WS with number ws090101.

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    Date of creation: Jan 2009
    Handle: RePEc:cte:wsrepe:ws090101
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    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. Peña, Daniel & Benito, Mónica, 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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