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

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3 Author(s)
Thibault, G. ; CMM-Centre de Morphologie Math., Math. et Syst., MINES ParisTech, Fontainebleau, France ; Angulo, J. ; Meyer, F.

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.

Published in:

Image Processing (ICIP), 2011 18th IEEE International Conference on

Date of Conference:

11-14 Sept. 2011