Shape from Silhouette (SFS) are methods used to estimate the 3D shape of objects from their silhouettes. The reconstructed shape, also called Visual Hull (V H), is the maximum volume which yields the silhouettes. As this volume is an upper bound, it contains objects and artifacts. Ghost connected components coming from artifacts are parts empty of real object. They provide non-pertinent data that interfere with many applications of SFS: motion capture, free-viewpoint rendering, etc. The more the object’s number increases, the more ghost-components appears. The problem is even worst with a small number of cameras. In this paper, we address the issue of detecting and removing ghost-components from any Visual Hull. Our method only needs cameras’ calibration and silhouette data. A formal description and several practical experimentation, show the efficiency of our approach. A comparison with previous methods underlines more accurate results, even using few cameras.