Abstract
Contour line is the main linear feature on topographic maps. Extraction of contour lines is tedious and time-consuming process, but is still an interesting problem. This paper presents a novel method for extracting contour lines from average-quality scanned topographic maps. First, it uses spatial fuzzy c-means algorithm (sFCM) to solve color aliasing and false color problems by taking into consideration both color and spatial information of topographic maps during color segmentation. In order to improve the categorizing rate, upper and lower cut-sets are introduced into sFCM. Second, to deal with the problem of thick lines, node segments are removed before gaps are repaired. Third, different methods are used to repair contour lines gaps according to the causes, which improves the break points matching accuracy. The performance of the method is tested on several topographic maps comparing with other methods, and the results show that the method can avoid misleading results caused by distortion and wrong branches at intersecting regions when using thinning algorithms and have more accurate and higher quality extraction results.
Cite
CITATION STYLE
Xu, B., Chen, J., & Yao, M. (2016). Identification of Contour Lines from Average-Quality Scanned Topographic Maps. Mathematical Problems in Engineering, 2016. https://doi.org/10.1155/2016/3089690
Register to see more suggestions
Mendeley helps you to discover research relevant for your work.