Size measurement of rocks is usually performed by manual sampling and sieving techniques. Automatic on-line analysis of rock size based on image analysis techniques would allow non-invasive, frequent and consistent measurement. In practical measurement systems based on image analysis techniques, the surface of rock piles will be sampled and therefore contain overlapping rock fragments. It is critical to identify partially visible rock fragments for accurate size measurements. In this research, statistical classification methods are used to discriminate rocks on the surface of a pile between entirely visible and partially visible rocks. The feature visibility ratio is combined with commonly used 2D shape features to evaluate whether 2D shape features can improve classification accuracies to minimize overlapped particle error.