Advanced statistical matrices for texture characterization: Application to DNA chromatin and microtubule network classification

Guillaume Thibault, Jesús Angulo, Fernand Meyer

Research output: Chapter in Book/Report/Conference proceedingConference contribution

8 Scopus citations

Abstract

This paper presents significant improvements of Gray Level Size Zone Matrix (GLSZM) which is a bivariate statistical representation of texture, based on the co-occurrences of size/intensity of each flat zone (connected pixels of the same gray level). The first improvement is a multi-scale extension of the matrix which merges various quantizations of gray levels. A second alternative is proposed to take into account radial distribution of zone intensities. The third variant is a generalization of the matrix structure which allows to analyze fibrous textures, by changing the pair intensity/size for the pair length/orientation of each region. The interest of these improved descriptors is illustrated by texture classification problems arising from quantitative cell biology.

Original languageEnglish (US)
Title of host publicationProceedings - International Conference on Image Processing, ICIP
Pages53-56
Number of pages4
DOIs
Publication statusPublished - 2011
Externally publishedYes
Event2011 18th IEEE International Conference on Image Processing, ICIP 2011 - Brussels, Belgium
Duration: Sep 11 2011Sep 14 2011

Other

Other2011 18th IEEE International Conference on Image Processing, ICIP 2011
CountryBelgium
CityBrussels
Period9/11/119/14/11

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Keywords

  • Gray Level Size Zone Matrix (GLSZM)
  • Structural Statistical Matrices
  • Texture Characterization

ASJC Scopus subject areas

  • Software
  • Computer Vision and Pattern Recognition
  • Signal Processing

Cite this

Thibault, G., Angulo, J., & Meyer, F. (2011). Advanced statistical matrices for texture characterization: Application to DNA chromatin and microtubule network classification. In Proceedings - International Conference on Image Processing, ICIP (pp. 53-56). [6116401] https://doi.org/10.1109/ICIP.2011.6116401