Segmentation d'images couleur par un opérateur gradient vectoriel ...

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QUANTIFICATION ET MORPHOLOGIE DE PHASES DE CLINKER PAR ANALYSE D'IMAGE. 150nm/picture element (pixel) is obtained and the digitising system can represent a high quality image. 2.5 IMAGE ANALYSIS Principe The object of this study was first of all to develop an image analysis programme to recognise the clinker phases. The algorithm was written in C-programming language, which supports graphical user interface tool kits and the digitiser board. It is most adapted to the digital image processing by its speed and compatibility with many tools developed in image processing. The applied algorithm works in two steps. It consists of a pre-segmentation of the matrix and the pores. From this segmentation, a mask is created for the alite and belite crystals to be classified in a second step. The result is the statistical composition of the clinker computed with all the acquired images (Figure 40). Figure 40. - Image analysis algorithm Matrix segmentation The chosen etching method colours alite and belite crystals and leaves the matrix clear, enabling the segmentation of this phase by a thresholding method. The histogram of a sample image shows two well-contrasted classes (Figure 41). WORLD CEMENT RESEARCH AND DEVELOPMENT 1998 98
QUANTIFICATION ET MORPHOLOGIE DE PHASES DE CLINKER PAR ANALYSE D'IMAGE. Figure 41. - Histogram of the grey levels of a sample image The presence of dark crystals (alite, belite) and the bright matrix can explain the bimodality. The optimal threshold to distinguish the regions is in the valley of the histogram. It is situated in the upper part of the grey-scale, but depends on the image lightning and cannot be determined a priori. The threshold value can be determined automatically with the method of Otsu [Otsu, 1979]. This algorithm maximises the inter-class-variance in the histogram to find out the optimal detection limit, as seen in Figure 41. The thresholding creates a binary image (Figure 42b). The bright matrix is white and the dark crystals are black. Actually, some clear picture elements in the alite may be wrongly counted as part of the matrix and some dark parts of the matrix are not detected. Thanks to the small size of such irregularities, it is possible to compensate them by region homogenisation. The applied filter is based on the mathematical morphology. This filter eliminates the extremely small objects and fills in some small holes in order to complete the segmentation of the matrix. A median filter and morphological dilatation and erosion are most adapted to this role. Figure 42 shows a sample image (a), the binary image after the thresholding (b) and the final segmentation of the matrix (c). WORLD CEMENT RESEARCH AND DEVELOPMENT 1998 99
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N° d’ordre 2001ISAL0062 Année 2
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TABLE DES MATIERES. 3. Gradient cou
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TABLE DES MATIERES. La cuisson et l
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INTRODUCTION GENERALE. Le Clinker e
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Chapitre 2 INTRODUCTION AU TRAITEME
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INTRODUCTION AU TRAITEMENT D'IMAGES
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Chapitre 3 GRADIENT COULEUR MULITEC
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GRADIENT COULEUR MULITECHELLE (GCM)
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Page 47 and 48: GRADIENT COULEUR MULITECHELLE (GCM)
Page 55 and 56: SEGMENTATION D’IMAGES PAR CONTOUR
Page 91 and 92: Chapitre 5 QUANTIFICATION ET MORPHO
Page 93 and 94: QUANTIFICATION ET MORPHOLOGIE DE PH
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Page 123 and 124: Chapitre 6 CONCLUSION GENERALE. C e
Page 125 and 126: ANNEXE A SCHEMA DE LA METHODE D’A
Page 127 and 128: ANNEXE B LA FABRICATION DU CIMENT.
Page 129 and 130: ANNEXE B LA FABRICATION DU CIMENT.
Page 131 and 132: ANNEXE C APPLICATIONS DU CALN A L'A
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Page 141 and 142: BIBLIOGRAPHIE [Beaudot, 1994] W. H.
Page 143 and 144: BIBLIOGRAPHIE [Hofmänner, 1975] F.
Page 145 and 146: BIBLIOGRAPHIE [Sapiro et al., 1996]
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