Rectilinear Shortest Paths and Minimum Spanning Trees in the Presence of Rectilinear Obstacles
IEEE Transactions on Computers
On the Generation of Skeletons from Discrete Euclidean Distance Maps
IEEE Transactions on Pattern Analysis and Machine Intelligence
Sequential Operations in Digital Picture Processing
Journal of the ACM (JACM)
Fast Euclidean distance transformation by propagation using multiple neighborhoods
Computer Vision and Image Understanding
Linear Time Euclidean Distance Algorithms
IEEE Transactions on Pattern Analysis and Machine Intelligence
Fast Euclidean distance transformation in two scans using a 3 × 3 neighborhood
Computer Vision and Image Understanding
2D Euclidean distance transform algorithms: A comparative survey
ACM Computing Surveys (CSUR)
Application of a 3NN+1 based CBR system to segmentation of the notebook computers market
Expert Systems with Applications: An International Journal
An Intelligent information segmentation approach to extract financial data for business valuation
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
Mining qualitative patterns in spatial cluster analysis
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
Mining co-distribution patterns for large crime datasets
Expert Systems with Applications: An International Journal
Hi-index | 12.05 |
Web maps have become an important decision making tool for our daily lives. We propose a flexible Web Map segmentation method in order to better use them for decision makings. We extend the distance transform algorithm to include complex primitives (point, line and area), Minkowski metrics, different weights and obstacles. The algorithms and proof are explained thoroughly and illustrated. Efficiency and error for the novel algorithms are also detailed. Finally, the usefulness of the algorithms is demonstrated through a series of real-life case studies.