The Research And Implementation On The Skeleton Feature Extraction Method For Terrain Model Based On Profile Recognition And Morphological Simplification

Geographic information processing is becoming increasingly important in today’svarious fields, but the original Digital Terrain Model (DTM) contains a lot of terrain features,such as ridge and valley lines. These features information plays an important role in dealingwith these data in the computer to recognize the terrain. The same time terrain features arealso essential for many engineering applications. However, due to factors such as the datastructure of a typical terrain data often not include these topographic features. So, how toextract the terrain features accurately has been the focus of current research.Since traditional skeleton feature extraction method PPA (Profile recognition andPolygon breaking Algorithm) are not able to extract the precise skeleton and special terrainfeature, a new profile recognition method combined with morphology is proposed to solvethese problems. In order to prevent the real target is not detected in the initial extraction, theprofile recognition is improved. Through the improved profile recognition algorithm can getthe original candidate feature point set. But there are a lot noise points in the set, a new profilerecognition method combined with morphology is proposed to solve the problems. Multiplemorphological codes are proposed to simplify the scale feature areas, and obtain the scalefeature lines. However, due to the impact of noise point, there may be some false skeletonfeature lines of loop at this time. In this paper, we solve this problem by defining three typesof loops and using the ring process algorithm what we proposed. Although the skeletonfeatures of terrain have been extracted by the above stages, the restoration algorithms forvector model are proposed to extract the skeleton feature lines to satisfy the requirementsabout vector skeleton features in the various fields. All of algorithms are conducted on manyreal experimental data, including GTOPO30and benchmark data provided by PPA to verifythe performance and accuracy of our method. The results showed our method precedes PPA asa whole.