Edge
detection is a fundamental step in image analysis. This is because edges characterize object boundaries useful
for identification of object in a scene. The importance of edge
detection increases as more people seek for automation in image processing systems. Determining bone edges is important because it can provide surgeons with important information for diagnosis, which in turn enables them to give better treatment decision to their patients. Many edge detectors have been developed and presently
wavelet transform is one of the popular approaches. This is because wavelet transform has the advantage of detecting edges using different scales. Edges can be represented and detected efficiently through its local maximum. This paper discusses the implementation of Cubic B-Spline wavelet on long bone x-ray images in detecting the edges using the local maxima modulus. Preliminary results show that this method can identify edges very well which can make it applicable to detect bone abnormalities.