NDLI: Automatic Extraction of Contour Lines from Topographic Maps

Content Provider	IEEE Xplore Digital Library
Author	Gul, S. Khan, M.F.
Copyright Year	2010
Abstract	The automatic extraction of contour lines and generation of digital elevation models (DEMs) from topographic maps is one of the challenging subjects mostly because of aliasing, false colors, closely spaced lines and other features causing intersection or overlapping. In this paper we present an algorithm to extract contour lines from colored images of scanned topographic maps. In our approach, we first segment the color image using adaptive thresholding to extract basic contour structure. Noise in the images is removed utilizing morphological operation. Next, the contour lines are reduced up to unitary thickness using Zhang’s thinning algorithm. The bifurcation and holes that result after thinning are removed using different masks. After thinning, end points of the broken contours are identified and best candidate for connection is determined, this is performed by analyzing the Euclidean distance and direction of end points near the gap. Then broken contour lines are joined employing curve fitting technique. The performance of the algorithm is tested on several samples of topographic maps and results show good segmentation of the contour lines. This automatic extraction algorithm for contour lines from topographic maps can save significant amount of time and labor as well as improving the accuracy of the contour line extraction.
Starting Page	593
Ending Page	598
File Size	909730
Page Count	6
File Format	PDF
ISBN	9781424488162
DOI	10.1109/DICTA.2010.105
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-12-01
Publisher Place	Australia
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	contour lines end points Noise Bifurcation bifurcation Image color analysis thinning adaptive thresholding Feature extraction Polynomials curve fitting Mathematical model Pixel holes
Content Type	Text
Resource Type	Article

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