Segmentation of bone surface in ultrasound images has numerous applications in computer aided orthopedic surgery. A robust bone surface extraction technique for ultrasound images can be used to non-invasively probe the bone surface. In this work, we present early results with an intuitive and computationally inexpensive bone segmentation approach. The prior knowledge about the appearance of bone in ultrasound images is exploited toward achieving robust and fast bone segmentation. Continuity and smoothness of the bone surface are incorporated in a cost function, which is globally minimized using dynamic programming. The performance of this method is evaluated on ultrasound images collected from two male cadavers. The images are segmented in about half a second making the algorithm suitable for real-time applications. Comparison between manual and automatic segmentation shows an average accuracy of less than 3 pixels (0.3 mm).