Uniqueness of the Gaussian Kernel for Scale-Space Filtering
IEEE Transactions on Pattern Analysis and Machine Intelligence
Scale-Based Description and Recognition of Planar Curves and Two-Dimensional Shapes
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Theory for Multiresolution Signal Decomposition: The Wavelet Representation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Boundary simplification in cartography preserving the characteristics of the shape features
Computers & Geosciences
Representing planar curves by using a scale vector
Pattern Recognition Letters
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This paper presents a method for smoothing noisy cartographic boundaries. The resulting smoothed description preserves the basic shape of the contour while smoothing out noise and unwanted detail. The performance of any simplification method relies on the quality of the levels of smoothing that represent the structures present. In our formulation the most important levels that best describe a given contour are determined by examining a measure of redundancy between each two successive smoothed curvature graphs along the boundary. These levels correspond to the locations of the local minima of such a measure of redundancy. Experimental results are presented showing that complicated planar curves such as cartographic boundaries can be smoothed to a high accuracy. It is proven also that an exaggerated noise added to the boundary can be handled by our method. The simplification therefore is reliable, robust, and very efficient.