a novel extension of the Local Binary Pattern description to surface tessellations based on the evolution of the color over concentric circles around a vertex. To determine these circles we adopt a sphere - edge intersection strategy and for this reason we name our approach edgeLBP. As application of the edgeLBP description, we propose the retrieval and classification of color patterns over surfaces.

The remainder of the paper is organized as follows. Section \[sec:star\] briefly reviews the literature on the retrieval of textured images and surfaces. Section \[sec:method\] introduces the elements of our method, i.e. the edgeLBP operator and how we store it in a descriptor. Section \[sec:results\] presents and analyses the retrieval and classification performances of the method over two datasets, while conclusive remarks end the paper, Section \[sec:conclusions\].

State of art {#sec:star}
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A typical strategy to detect textures on images is to consider local patches that describe the behavior of the texture around a group of pixels. Examples of these descriptions are the Local Binary Patterns (LBP) [@ojala; @ojala02], the Scale Invariant Feature Transform (SIFT) [@Lowe2004] and the Histogram of Oriented Gradients (HOG) [@DaTr05].The generalization of these descriptions to (even textured) surfaces has been explored in several 