Tavana Mert
The visualization of 3D scanned point clouds is a crucial aspect of many applications, including computer graphics, engineering, and cultural heritage preservation. One of the key challenges in rendering point cloud data is effectively highlighting the edges of objects within the scan, as edges provide essential structural and geometric information. Traditional visualization methods often struggle with clarity, especially in high-density point clouds, leading to difficulties in perceiving object boundaries. To address this issue, a dual 3D edge extraction approach can be employed to enhance edge visibility, improving the overall clarity and interpretability of point cloud data. Edge highlighting in point clouds is complex due to the unstructured nature of the data. Unlike structured meshes, which consist of predefined connectivity, point clouds are collections of discrete points without explicit connectivity information. This lack of structure necessitates the development of specialized edge detection and enhancement techniques. The dual 3D edge extraction method involves identifying edges using two complementary approaches: geometricbased edge detection and feature-based edge extraction. By combining these methods, a more robust and visually appealing edge-enhancement technique can be achieved.
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Telecommunications System & Management received 109 citations as per Google Scholar report
