Abstract: A method for encoding a non-manifold polygonal mesh operates by converting an original (non-manifold) model to a manifold model, encoding the manifold model using a mesh compression technique, and clustering, or stitching together during a decompression process, vertices that were duplicated earlier to faithfully recover the original connectivity. By separating the connectivity from model geometry and properties, the method avoids encoding vertices (and properties bound to vertices) multiple times. This provides a reduction in the size of the bit-stream compared with encoding the model as a manifold.

Abstract: A data structure for representing a general n-dimensional polygonal mesh. The data structure includes a structure record and a data record for each three dimensional shape. The structural record contains polygonal model connectivity information and further includes a stitching record that defines corresponding polygonal (triangular) mesh edge pairs and a polygonal (triangular) tree record representing a polygon (triangle) tree. The stitching record includes a vertex tree and a set of jump edges. The data record includes at least three polygonal records, each corresponding to a polygon. Each polygonal record is associated with a face of said polygonal model and classifies its corresponding polygon as either a leaf polygon, a running polygon or a branching polygon. Polygonal shapes are encoded into the data structure by first building a spanning tree for the polygonal mesh. A set of cut edges are derived for the polygonal mesh. The stitching record is constructed for the set of cut edges.

Abstract: A system and method extracts object boundaries in computed tomography images that have been corrupted by noise. The system and method find object boundaries in tomography images by finding edges in sinogram data, thereby providing a segmentation method that is insensitive to the image noise introduced by the process of image reconstruction from projections. The boundary-detection system uses projection data, and optionally tomographic image data, to detect the boundaries of objects in tomographic images. The system is of particular value for boundary-detection in images corrupted by reconstruction artifacts, such as CT scans of hospital patients who have implanted metal prostheses. The system is applicable to recovering the boundaries of convex objects, and the convex segments of the boundaries of concave objects (though not the complete boundaries of the concave objects themselves).