The segmentation of video sequences into shots is the first step towards video content analysis. Two kinds of shot boundaries can be distinguished: abrupt scene changes ("cuts") and gradual transitions. In this paper, we present a technique to reduce the error rates of cut detection algorithms based on pixel-wise or histogram-based frame difference metrics when operating directly on compressed MPEG video data. The proposed approach, called "frame difference normalization" (FDN), intends to eliminate the effects of a specific frame pattern in MPEG streams responsible for causing such errors. Experimental results will be presented to demonstrate the benefits of our proposal and its superiority over a more general noise filter. Furthermore, the proposed method is not limited to a particular algorithm but it is applicable to an entire class of cut detection algorithms.