A target composed of random dots can be easily segmented from a background of random dots when each is defined by a different, broad distribution of dot speeds, colours, or brightnesses, even if these distributions overlap extensively. This shows that segmentation can be based on global properties of the target and background. If average feature value is the relevant global property, segmentation threshold should be a monotonically decreasing function of dot density. Observers viewed a 6.5 deg × 6.5 deg square array of between 512 and 36 864 randomly positioned dots (dot size 4.7 or 1.6 min arc) in which the target was a vertical band of dots defined by a different distribution of luminance, colour, or motion from the background. The task was to indicate whether the target appeared on the left or on the right of midline. The stimulus was displayed for 67 ms, followed after 233 ms by a 67 ms mask. We found that motion segmentation thresholds decrease monotonically as a function of density. For luminance and colour, segmentation thresholds initially decrease toward a local minimum, then increase to a local maximum. Thereafter, thresholds decrease monotonically as density increases further. These results suggest that the integrative segmentation process for motion is qualitatively different from those for luminance and colour. The local extrema for luminance and colour suggests that segmentation in these domains is based on forming clusters by linking together dots with similar feature properties. Only when interdot distance is sufficiently small are all dots within an area included in the cluster. Behaviour is then determined by difference in average feature value or target — background contrast.