In scene analysis, the availability of an initial background model that describes the scene without foreground objects is at the basis of many computer vision applications. Multi-modal models of the scene background are frequently adopted in the applications, where each mode tries to keep track of the multiple background modes observed along the sequence. In this work we specifically address the problem of extracting a single background image by a multi-modal model of the scene background, in order to compare it against a given ground truth image of the background. Experimental results are provided on the SBMnet dataset, based on an existing multi- model background model and different extraction criteria, and general conclusions are drawn.