Prakt. Met. Sonderband 38 (2006) 95 
LOM and 6. SUMMARY AND OUTLOOK 
grains are 
It. Using only light optical microscopy (LOM), the characterization of multiphase steels cannot 
mination, be achieved sufficiently due to the fact that very fine metallographic constituents are 
separate present, which are smaller than the optical resolution limit. This problem can be avoided by 
fication is using scanning electron microscope (SEM) images of a higher resolution in addition to the 
light optical images. 
Common commercial pixel - based software programs for metallographic applications are 
not able to analyse the phases in multiphase steels correctly. Problems occur due to the 
usage of only the grey value in the observed image, during the classification process. If 
there are small differences in grey values, the different metallographic constituents cannot 
be separated from each other and a correct quantification is not possible using pixel - 
based algorithms. Therefore, a new approach was developed for the analysis and 
quantification of these steels. 
Within this work, a method for automatic composing LOM images and SEM images into a 
single feature image is described. A novel segment based approach for the analysis of 
multiphase steel images is presented. Based on the composed feature image and its 
gradient images, segments are calculated, which provide information about the shape of 
ferrite and martensite. In addition, about 40 different features are provided by the 
calculated segments in conjunction with the feature images. Thereby, contour, optical and 
texture features as well as mean and variance values of the original and gradient images 
and, in addition, neighbourhood relations, are derived. These features are used for the 
classification of martensite and ferrite phases, using a Bayesian classificatory. 
This segment based image analysing approach can be used for image analysis of various 
materials. Pictures like EBSD, optical pictures from different etchings and SEM pictures 
nase steel can be added to each other to provide image information from different receiving 
and SEM technologies and make them useable for quantification. 
tis about For future work even more features can be used for classification. A higher amount of 
groundtruth — data will result in a better classification. Also more complex multiphase 
Cs can be steels with a higher amount of metallographic constituents like TRIP steels could be 
analysed and quantified by this method. In this way a new method is available meet 
challenges in metallographic characterisation of complex materials 
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