Human ability to perceive surface shapes plays a crucial role in understanding their surrounding objects and environments. Although the sense of vision has been employed frequently for virtual shape perception, it is desirable to enhance performance of shape perception in the three-dimensional (3D) virtual environments (VEs) by providing haptic feedback. To explore how well the human ability is to discriminate surface shapes under haptic feedback, the experiment presented in this thesis applied a novel force model, which was created by our research lab, to distinguish four kinds of sinusoidal virtual surfaces, which have various amplitudes differing from a flat surface. The main finding is that Just Noticeable Difference (JND) range of amplitude was around 1.19 - 1.95 mm for distinguishing sinusoidal virtual surfaces from flat ones. This finding quantifies the human ability to discriminate virtual surfaces, and may contribute to fundamental knowledge for creating applications with haptic interactions.