In this paper, the problem of detecting particular underwater structures, e.g., anodes used to join together separated sections of a pipeline, from visual images is addressed. Images are acquired by an autonomous underwater vehicle during sea-bottom surveys for pipeline inspection. Anodes with different characteristics, e.g., material, size, color, etc., can be found on the same pipeline but all are characterized by the same visual feature, i.e., an elliptical arc. To this end, a voting-based method able to detect elliptical arcs on the image plane is used to locate accurately anodes along the pipeline. Three dimensional (3D) geometric information about the scene, e.g., 3D equations of the pipeline borders, is used to reduce from 5 to 2 the dimensions of the parametric space needed for ellipse detection. Then, among the instances of detected ellipses on the image plane, false elliptical arcs, which are not compatible with the 3D scene geometry, are eliminated. Finally, the detection of consecutive true elliptical arcs over a long image sequence is used to infer the presence of an anode. Experimental tests on large sets of real underwater images have been performed to evaluate the effectiveness and the robustness of the method.