Study on Segmentation of Measured Data with Noise in Reverse Engineeing

The segmentation has been performed to the data of good quality in most cases, so the adoption of previous segmentation theory to the measured data with a laser scanner does not produce good result because of the characteristics of the data with noise component. A new approach to perform the segmentation on the scanned data is introduced to deal with problems during reverse engineering process. A triangular net is generated from measured point data, and the segmentation on it is classified as plane, smooth and rough segment. The segmentation result in each segment depends on the user-defined criteria. And the difference of the segmentation between the data of good quality and the data with noise is described and analyzed with several real models. The segment boundaries selected are used to maintain the characteristics of the parts during modeling process, thus they contribute to the automation of the reverse engineering.