Shape and texture indexes application to cell nuclei classification

Guillaume Thibault, Bernard Fertil, Claire Navarro, Sandrine Pereira, Pierre Cau, Nicolas Levy, Jean Sequeira, Jean Luc Mari

Research output: Contribution to journalArticle

67 Scopus citations

Abstract

This paper describes the sequence of construction of a cell nuclei classification model by the analysis, the characterization and the classification of shape and texture. We describe first the elaboration of dedicated shape indexes and second the construction of the associated classification submodel. Then we present a new method of texture characterization, based on the construction and the analysis of statistical matrices encoding the texture. The various characterization techniques developed in this paper are systematically compared to previous approaches. In particular, we paid special attention to the results obtained by a versatile classification method using a large range of descriptors dedicated to the characterization of shapes and textures. Finally, the last classifier built with our methods achieved 88% of classification out of the 94% possible.

Original languageEnglish (US)
Article number1357002
JournalInternational Journal of Pattern Recognition and Artificial Intelligence
Volume27
Issue number1
DOIs
StatePublished - Feb 2013

Keywords

  • Shape and texture indexes
  • classification
  • gray level size zone matrix
  • shape and texture characterization

ASJC Scopus subject areas

  • Software
  • Computer Vision and Pattern Recognition
  • Artificial Intelligence

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