Algorithmic graph theory
Maris: map recognition input system
Pattern Recognition
Image Filtering, Edge Detection, and Edge Tracing Using Fuzzy Reasoning
IEEE Transactions on Pattern Analysis and Machine Intelligence
Learning and Design of Principal Curves
IEEE Transactions on Pattern Analysis and Machine Intelligence
Piecewise Linear Skeletonization Using Principal Curves
IEEE Transactions on Pattern Analysis and Machine Intelligence
A System for Interpretation of Line Drawings
IEEE Transactions on Pattern Analysis and Machine Intelligence
A k-segments algorithm for finding principal curves
Pattern Recognition Letters
Automatic parameter selection for a k-segments algorithm for computing principal curves
Pattern Recognition Letters
Extraction of curvilinear features from noisy point patterns using principal curves
Pattern Recognition Letters
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Principal curves detection is an essential processing in computer vision and pattern recognition with many important applications. In this paper, we present a new method to detect principal curves in complicated feature images. Based on the criteria of the shortest path of curves and directional deviation of paths, principal curves detection is carried out in graph domain. DFS searching scheme is adopted in exploration of a graph network.The motivation of this research is to find road boundaries and house contours from printed map images. Since characters and map symbols often overlap with useful image features, the algorithm of principal curves detection aims to obtain "clean" feature images from the original maps. By extensive experiments, the algorithm has shown good efficiency and robustness with real map images. The technique described in this paper can also be used in other applications, such as in character recognition, to separate characters from other unwanted document components lying on the characters.