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A Novel Approach for Raster Data Vectorization

Raster data vectorization is one of the key techniques for the integration of remote sensing and GIS.Although it's a traditional problem with a lot of algorithm proposed,there still exist many defects including,e.g.,the problem of the "island",especially the multi-nested "island" in many vectorizing methods.In this paper,an improved algorithm for raster data vectoriation is proposed.This method includes four main steps.The first step is to extract the vertices and nodes.Moving through the image using a 2×2 template window,we can extract the vertices and nodes and their connection information.The second step is to construct the arcs.We use the connection information to construct the non-closed and closed arcs.The third step is to build the polygons.With left-turn algorithm,we can build simple polygons from non-closed arcs.Besides,since closed arcs correspond to simple polygons,we only have to convert a vertex of an arc to a vertex of a polygon.The last step is to deal with the "islands".We judge containing relationship among these polygons.Since a polygon may be contained by several parent polygons,we should find its minimal containing parent and then deal with the "islands".The main advantages of the proposed algorithm include the follows.1) Algorithm efficiency is relatively fast.2) It isn't sensitive to the size of raster data,but only sensitive to the number of the nodes and vertexes.3) It can build the correct topology and then solve the problem of multi-nested "island".Our method is validated with many successful experiments when applied in vectorizing the remote sensing classification imagery.