2 - Matrice de co-occurrence optimale pour la segmentation automatique d'images ultrasonores
1992
This paper introduces a new method of segmentation using automatic
thresholding adapted to the NDT ultrasonic images . This study is based
on image analysis through co-occurrence matrixes . It shows an optimization
of the r and 0 parameters of the co-occurrence matrix enabling to
define more acurately the border between noise and defect echoes . The
segmentation is obtained by automatically taking into account a threshold
derived from a determination curve calculated front the co-occurrence
matrix . This curve, called Average Product of Variances Measure, is an analysis of the distribution of the matrix coefficients . The results show
behaviors of the co-occurrence matrixes and of the threshold selection
curves that justify perfectly the analysis performed on the characteristics
of the image .
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