DocumentCode :
39708
Title :
Advanced Statistical Matrices for Texture Characterization: Application to Cell Classification
Author :
Thibault, Guillaume ; Angulo, J. ; Meyer, Folker
Author_Institution :
Center for Math. Morphology, MinesParisTech, Fontainebleau, France
Volume :
61
Issue :
3
fYear :
2014
fDate :
Mar-14
Firstpage :
630
Lastpage :
637
Abstract :
This paper presents new structural statistical matrices which are gray level size zone matrix (SZM) texture descriptor variants. The SZM is based on the cooccurrences of size/intensity of each flat zone (connected pixels with the same gray level). The first improvement increases the information processed by merging multiple gray-level quantizations and reduces the required parameter numbers. New improved descriptors were especially designed for supervised cell texture classification. They are illustrated thanks to two different databases built from quantitative cell biology. The second alternative characterizes the DNA organization during the mitosis, according to zone intensities radial distribution. The third variant is a matrix structure generalization for the fibrous texture analysis, by changing the intensity/size pair into the length/orientation pair of each region.
Keywords :
DNA; biological techniques; biology computing; cellular biophysics; fluorescence; image classification; image texture; molecular biophysics; statistical analysis; DNA organization; advanced statistical matrices; cell classification; fibrous texture analysis; fluorescence; gray level size zone matrix texture descriptor variants; information processing; intensity-size pair; length-orientation pair; matrix structure generalization; mitosis; multiple gray-level quantizations; quantitative cell biology; structural statistical matrices; supervised cell texture classification; zone intensities radial distribution; DNA; Data models; Feature extraction; Materials; Quantization (signal); Training; Vectors; Gray-level size zone matrix (SZM); quantitative cytology; structural statistical matrices; texture characterization and classification;
fLanguage :
English
Journal_Title :
Biomedical Engineering, IEEE Transactions on
Publisher :
ieee
ISSN :
0018-9294
Type :
jour
DOI :
10.1109/TBME.2013.2284600
Filename :
6621011
Link To Document :
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