ROAMing terrain: real-time optimally adapting meshes
VIS '97 Proceedings of the 8th conference on Visualization '97
A Semiautomatic Method for Assigning Elevation in Contour Maps
IEEE Transactions on Knowledge and Data Engineering
Contour Line Extraction from Color Images of Scanned Maps
ICIAP '97 Proceedings of the 9th International Conference on Image Analysis and Processing-Volume I - Volume I
Contour Lines and DEM: Generation and Extraction
DEM '01 Proceedings of the First International Symposium on Digital Earth Moving
Geometry clipmaps: terrain rendering using nested regular grids
ACM SIGGRAPH 2004 Papers
Proceedings of the 11th International Conference of the NZ Chapter of the ACM Special Interest Group on Human-Computer Interaction
| Hi-index | 0.00 |
Terrains are an essential part of outdoor environments. Terrain models are important for computer games and applications in architecture, urban design and archaeology. A popular and intuitive way to represent terrains is by contour maps. In order to render such representations in 3D the contours must be labelled with height values and converted to Digital Elevation Maps (DEM), which are regular grids of height values and are represented as gray scale images. The labelling of contour lines is time intensive for large maps and prone to errors. In this paper we present an efficient and novel algorithm for semi-automatically labelling contour maps and for converting them to DEMs. The algorithm first identifies point extrema which must be labelled by the user. The point extrema are connected by a graph and the contour lines crossed by edges are labelled automatically. We show that ambiguities can exist for so-called line extrema. Our algorithms will resolve ambiguous regions requiring a minimal number of additional user inputs. We also present a more efficient graph representation, which requires about 10--20% more user inputs than the optimal case. After the contour lines are labelled, the contour map is triangulated and the height value at each point of the DEM is computed using a bilinear interpolation. The presented algorithm is efficient, requires minimal user inputs, and produces good quality DEMs. We present several examples, discuss its suitability for different applications, and provide a complexity analysis.