Multi-resolution and slice-oriented feature extraction and segmentation of digitized data

Given an object digitized as sequences of scan lines, we propose an approach to the extraction of feature lines and object segmentation based on a multi-resolution representation and analysis of the scan data. First, the scan lines are represented using a multi-resolution model which provides a flexible and useful reorganization of the data for simplification purposes and especially for the classification of points according to their level of detail, or scale. Then, scan lines are analyzed from a geometrical point of view in order to decompose each profile into basic patterns which identify 2D features of the profile. Merging the scale and geometric classification, 3D feature lines of the digitized object are reconstructed tracking patterns of similar shape across profiles. Finally, a segmentation is achieved which gives a form-feature oriented view of the digitized data. The proposed approach provides a computationally light solution to the simplification of large models and to the segmentation of object digitized as sequences of scan lines, but it can be applied to a wider range of digitized data.