Object segmentation is a crucial task for image analysis and has been studied widely in the past. Most segmentation algorithms rely on changes in contrast or on clustering the same colors only. Yet there seem to be no real one-and-for-all solution to the problem. Nevertheless graph-based energy minimization techniques have been proven to yield very good results in comparison to other techniques. They combine contrast and color information into an energy minimization criterion. We give a brief overview of two recently proposed techniques and present some enhancements to them. Furthermore a combination of them into the
algorithm leads to suitable results for segmenting objects in infrared images.