Introduction to statistical pattern recognition (2nd ed.)
Introduction to statistical pattern recognition (2nd ed.)
Watersheds in Digital Spaces: An Efficient Algorithm Based on Immersion Simulations
IEEE Transactions on Pattern Analysis and Machine Intelligence
Recognition of Digits in Hydrographic Maps: Binary Versus Topographic Analysis
IEEE Transactions on Pattern Analysis and Machine Intelligence
Perceptual grouping for symbol chain tracking in digitized topographic maps
Pattern Recognition Letters
Discrete Mathematical Structures for Computer Science
Discrete Mathematical Structures for Computer Science
Handbook of AI
IEEE Transactions on Pattern Analysis and Machine Intelligence
Direct Gray-Scale Extraction of Features for Character Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
Automatic Interpretation of Scanned Topographic Maps: A Raster-Based Approach
GREC '97 Selected Papers from the Second International Workshop on Graphics Recognition, Algorithms and Systems
Automatic extraction of road intersection position, connectivity, and orientations from raster maps
Proceedings of the 16th ACM SIGSPATIAL international conference on Advances in geographic information systems
Advances in Engineering Software
Augmenting cartographic resources for autonomous driving
Proceedings of the 17th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems
Classification of raster maps for automatic feature extraction
Proceedings of the 17th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems
Segmentation of colour layers in historical maps based on hierarchical colour sampling
GREC'09 Proceedings of the 8th international conference on Graphics recognition: achievements, challenges, and evolution
A new approach to the reconstruction of contour lines extracted from topographic maps
Journal of Visual Communication and Image Representation
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This paper presents a method for the extraction of contour lines and other geographic information from scanned color images of topographical maps. Although topographic maps are available from many suppliers, this work focuses on United States Geological Survey (USGS) maps. The extraction of contour lines, which are shown with brown color on USGS maps, is a difficult process due to aliasing and false colors induced by the scanning process and due to closely spaced and intersecting/overlapping features inherent to the map. These difficulties render simple approaches such as clustering ineffective. The proposed method overcomes these difficulties using a multistep process. First, a color key set, designed to comprehend color aliasing and false colors, is generated using an eigenvector line-fitting technique in RGB space. Next, area features, representing vegetation and bodies of water, are extracted using RGB color histogram analysis in order to simplify the next stage. Then, linear features corresponding to roads and rivers including contours, are extracted using a valley seeking algorithm operating on a transformed version of the original map. Finally, an A* search algorithm is used to link valleys together to form linear features and to close the gaps caused by intersecting features. The performance of the algorithm is tested on a number of USGS topographic map samples.