92 Prakt. Met. Sonderband 38 (2006) 
3. SEGMENTATION 
Using only the combined feature image of the LOM and SEM images, a classification Aft 
process can not be directly achieved. An intermediate segmentation step is necessary, in or 
order to extract more information about the phases. sec 
Aim of the segmentation is the combination of neighbouring pixels, with similar properties, wh 
into segments. It is desired, that the derived segments correspond to different phases, so im: 
pixels of different phases, have to be merged into different segments. Otherwise the the 
phases can not be separated from each other during the following classification process. Fo 
Various features of the calculated segments can be extracted from the segmented image 
and this information mainly supports the subsequent classification process. 
To reduce calculation time a pre-filtration with the Mean Shift Algorithm [4] is applied 
before segmentation, where small noise is smoothed and sharp edges rest in the image. 
For the segmentation process, the Water Shed Algorithm [5] is used. It is an edge based 
segmentation method which uses the gradient image of combined image. For each local 
minimum within the gradient image, a segment is generated. Although a noise reducing Th 
prefiltering was applied to the combined image, the Water Shed Algorithm leads to an over fea 
segmentation. That's why a subsequent merging step, where similar adjacent segments Th 
are combined, is necessary. ma 
The criteria for a subsequent merging process are: dis 
- Difference in grey value of neighbouring segments cla 
Shared contour length/contour length cal 
Average value in the gradient image of the combined picture on the common contour of Th 
neighbouring segments Th 
fe: 
Figure 5: Result of segmentation after pre-filtration, segmentation and merging 
In Figure 5 is the result of segmentation shown. The representation of ferrite and 
martensite in single segments was successful. The pixels of different phases in the image 
of the multiphase steel are merged in different segments. Various features from segments Th 
are extracted and can be used for classification. mil 
Ar 
en 
Cl: