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QUANTIFICATION ET MORPHOLOGIE DE PHASES DE CLINKER PAR ANALYSE D'IMAGE. 2.6 EXPERIMENTAL RESULTS & DISCUSSIONS The validation of the system is made in two steps: firstly, the validation of the automatic crystal classification in the image, and secondly, the comparison of the clinker composition determined by automatic analysis with the classical point counting method. Three representative clinkers from the Lafarge laboratory with different origins and characteristics were analysed. For the image analyser, 50 images in the clinker were selected randomly. This involved the classification of about 18 000 test-points in each clinker. Table 1 shows the results obtained by automatic classification. The second column (b) of each clinker gives a reference value. It presents the statistic composition computed with the same images, when an expert manually corrected the classification errors of the automatic method. The difference between column a) and b) measures the efficiency of the automatic image analysis and segmentation. The small difference between the values ensures that it is possible to recognise the crystal phases in the clinker with a good precision. Table 2 compares the composition obtained by automatic analysis of 50 images (a) and by classical counting of 2000 points by an expert in the Lafarge laboratory (b). In the manual technique, two points are placed in a distance of 100µm, and they are never located in the same crystal. Our counting approach differs by a smaller distance (5µm) between the points. Several points are taken in the same crystal. Table 1. Classification results of the algorithm for three test clinkers (mass percentage) a) automatic classification, b) automatic classification & expert correction. Clinker 1 Clinker 2 Clinker3 Crystals: a) b) a) b) a) b) Alite 54.3 % 52.8 % 57.9 % 59.5 % 53.8 % 57.7 % Belite 21.1 % 24.5 % 20.3 % 21.9 % 29.0 % 24.1 % Matrix 24.6 % 22.7 % 21.8 % 18.6 % 17.2 % 18.2 % Table 2. Comparison of the point counting and the automatic classification (mass percentage) a) automatic classification, b) point counting. Clinker 1 Clinker 2 Clinker3 Crystals: a) b) a) b) a) b) Alite 54.3 % 57.3 % 57.9 % 68.3 % 53.8 % 58.8 % Belite 21.1 % 24.0 % 20.3 % 17.3 % 29.0 % 24.0 % Matrix 24.6 % 18.7 % 21.8 % 14.4 % 17.2 % 17.2 % The results on clinker 1 were comparable. For the second one, a significant difference in the contents of alite is not caused by the failure of the image classification (results in Table 1 are nearly the same for automatic and corrected classification), but it is caused by the choice the 50 images of the clinker. The number of 50 images or the choice of these images was not as WORLD CEMENT RESEARCH AND DEVELOPMENT 1998 106
QUANTIFICATION ET MORPHOLOGIE DE PHASES DE CLINKER PAR ANALYSE D'IMAGE. representative for the clinker as the 2000 points manually counted by the expert, which cover a larger analysis domain. For the analysis, two different magnifications were tested. The analysis of clinker 1 and 2 used an examination field of 95µm*125µm for each image. The 50 fields of clinker 3 were taken with a less important magnification. Each image represents a field of 240µm*315µm. This corresponds to at least 40 crystals. The examination field is about six times bigger than in the case of clinker 1 and 2. The bigger field represents the clinker more correctly and the examination points are placed in a higher distance of 13µm. In the case of the reduced magnification, the dimensions (measured in picture elements) of each crystal in the image are less important. Thus, automatic colour and texture classification works with a local window of a smaller size. This decreases the performance of the automatic classification observed in Table 1. The difference between column a) and b) is more important for clinker 3 than for clinker 1 and 2. For the future, the solution will be either to increase the number of images with the bigger magnification to obtain a statistically significant sample or to increase the performance of the classification method to obtain good results with a less important magnification. 2.7 CONCLUSIONS The object of this paper was the automatic quantitative determination of the phases of Portland cement clinker using a computer imaging system. The applied methods are based on advanced texture and colour analysis. The automatic segmentation of the phases takes advantage on the characteristics of local windows. The decision is made using data fusion from separated colour and texture classifications. The presented software determines the percentage of the main clinker phases. The proposed method gives access to the results manually obtained by the expert on different clinker types. The automatic phase segmentation between alite and belite gives good results. The system is integrated in a user interface, which makes the clinker analysis easy to be used even by a less experienced operator. The complete system can use the acquired images twice. Besides the use for the phase distribution analysis, the images can be used for the crystal size measurement. The automatic system is installed in the Lafarge laboratory in Viviers (France) and is used as a routine tool for the microscopic analysis. It permits to considerably reduce the time needed for the analysis of the different clinker samples. The system can replace the classical hard and tiring work and gives new possibilities to the clinker microscopy. The manual modification of wrong classed points is possible by the open and interactive software design by a simple mouse click. The corrections can be used to optimise the classifier. This can be made by adaptation of the parameters used for the texture analysis or by amelioration of the learning database. In an additional developing state of the system, the automatic crystal measurement and form determination will be integrated. This could bring new information about the clinker and increase the performance of the quality control. Also, the determination of the minor phase WORLD CEMENT RESEARCH AND DEVELOPMENT 1998 107
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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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