Document image segmentation algorithms primarily aim at separating text and graphics in presence of complex lay- outs. However, for many non-Latin scripts, segmentation becomes a challenge due to the characteristics of the script. In this paper, we empirically demonstrate that successful al- gorithms for Latin scripts may not be very effective for Indic and complex scripts. We explain this based on the differ- ences in the spatial distribution of symbols in the scripts. We argue that the visual information used for segmenta- tion needs to be enhanced with other information like script models for accurate results.