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 fuzzyc-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.
Highlights
Topographic maps are carriers of spatial information
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
Research on automatic identification and extraction of contour lines on maps has a long history and involves a variety of methods. These methods have produced good results for some high-quality topographic maps, but the results are not satisfactory for low-quality maps, mainly due to the following three problems [5]: (1) color aliasing and false colors on scanned maps due to poor paper or printing quality and the performance of the scanner (on a 96-dot-per-inch (DPI) resolution map, most contour lines are 2 to 4 pixels in width; color deviation occupies a large portion in pixels of lines); (2) conglutination of adjacent lines to form thick lines in some areas of a scanned map where contour lines are densely distributed [6]; (3) a large number of contour lines gaps caused by intersecting and overlapping information on a topographic map after color segmentation
Summary
Topographic maps are carriers of spatial information. Contour lines, as special information signs on topographic maps, reflect regional landform features on topographic maps [1, 2]. Research on automatic identification and extraction of contour lines on maps has a long history and involves a variety of methods These methods have produced good results for some high-quality topographic maps, but the results are not satisfactory for low-quality maps, mainly due to the following three problems [5]: (1) color aliasing and false colors on scanned maps due to poor paper (such as paper turning yellow over time) or printing quality and the performance of the scanner (on a 96-dot-per-inch (DPI) resolution map, most contour lines are 2 to 4 pixels in width; color deviation occupies a large portion in pixels of lines); (2) conglutination of adjacent lines to form thick lines in some areas of a scanned map where contour lines are densely distributed [6]; (3) a large number of contour lines gaps caused by intersecting and overlapping information on a topographic map after color segmentation. Mathematical Problems in Engineering the proposed method has the following features: (1) upper and lower cut-sets are introduced to improve the categorizing rate when using spatial fuzzy c-means (sFCM) algorithm to solve color aliasing and false colors; (2) it deals with the problem of thick lines by removing node segments, with more accurate results; (3) according to the causes of gaps, different methods are used to repair gaps to obtain maps with continuous and complete contour lines
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