Cluster in images

• Autores: M. Andrea Giuliodori, Rosa Elvira Lillo Rodríguez , Daniel Peña Sánchez de Rivera
• Localización: XXXI Congreso Nacional de Estadística e Investigación Operativa ; V Jornadas de Estadística Pública: Murcia, 10-13 de febrero de 2009 : Libro de Actas, 2009, ISBN 978-84-691-8159-1
• Idioma: inglés
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• Resumen

  • A color image is mathematically composed of a set of three matrices that represent the color intensity of the pixels that constitute the whole image. By considering that every matrix is composed of variables and observations, we can use the classic multivariate data analysis as a tool for the statistical interpretation of a picture. In particular, one of the goals in exploratory image analysis is to classify images without eye observation. In this work, we analyze and interpret the statistical structure of an image in order to nd distinctive features to build clusters. We show a general method to classify and group the pictures considering three classi cation variables: the local variability, the e ective variance and the spatial correlation.