Modeling visual search on a rough surface

The LNL (linear, non-linear, linear) model has previously been successfully applied to the problem of texture segmentation. In this study we investigate the extent to which a simple LNL model can simulate human performance in a search task involving a target on a textured surface. Two different classes of surface are considered: 1/f(beta)-noise and near-regular textures. We find that in both cases the search performance of the model does not differ significantly from that of people, over a wide range of task difficulties.