  In this paper, we propose a new texture analysis method using the
deterministic partially self-avoiding walk performed on maps modified with
thresholds. In this method, two pixels of the map are neighbors if the
Euclidean distance between them is less than $\sqrt{2}$ and the weight
(difference between its intensities) is less than a given threshold. The maps
obtained by using different thresholds highlight several properties of the
image that are extracted by the deterministic walk. To compose the feature
vector, deterministic walks are performed with different thresholds and its
statistics are concatenated. Thus, this approach can be considered as a
multi-scale analysis. We validate our method on the Brodatz database, which is
very well known public image database and widely used by texture analysis
methods. Experimental results indicate that the proposed method presents a good
texture discrimination, overcoming traditional texture methods.
