Publication | Closed Access
Advanced Statistical Matrices for Texture Characterization: Application to Cell Classification
283
Citations
30
References
2013
Year
EngineeringBiometricsDermatoglyphicAdvanced Statistical MatricesImage ClassificationImage AnalysisFlat ZonePattern RecognitionBiostatisticsTexture Descriptor VariantsCell Texture ClassificationMachine VisionMedical ImagingHistopathologyStatistical Pattern RecognitionMedical Image ComputingCell BiologyComputer VisionMicroscope Image ProcessingBioimage AnalysisTexture AnalysisSystems BiologyMedicineCell Detection
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.
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