Combinatorial optimization: algorithms and complexity
Combinatorial optimization: algorithms and complexity
Using consensus sequence voting to correct OCR errors
Computer Vision and Image Understanding
Uniform Distribution, Distance and Expectation Problems for Geometric Features Processing
Journal of Mathematical Imaging and Vision
Topology of strings: median string is NP-complete
Theoretical Computer Science
Average brain models: a convergence study
Computer Vision and Image Understanding - Special issue on analysis of volumetric image
On Median Graphs: Properties, Algorithms, and Applications
IEEE Transactions on Pattern Analysis and Machine Intelligence - Graph Algorithms and Computer Vision
International Journal of Computer Vision - Joint special issue on image analysis
An approximate median search algorithm in non-metric spaces
Pattern Recognition Letters
Fast Median Search in Metric Spaces
SSPR '98/SPR '98 Proceedings of the Joint IAPR International Workshops on Advances in Pattern Recognition
GbRPR'03 Proceedings of the 4th IAPR international conference on Graph based representations in pattern recognition
Exploring the performance limit of cluster ensemble techniques
SSPR&SPR'10 Proceedings of the 2010 joint IAPR international conference on Structural, syntactic, and statistical pattern recognition
A class of generalized median contour problem with exact solution
SSPR'06/SPR'06 Proceedings of the 2006 joint IAPR international conference on Structural, Syntactic, and Statistical Pattern Recognition
Generalized median string computation by means of string embedding in vector spaces
Pattern Recognition Letters
Ensemble clustering by means of clustering embedding in vector spaces
Pattern Recognition
Pattern Recognition Letters
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The computation of generalized median patterns is typically an NP-complete task. Therefore, research efforts are focused on approximate approaches. One essential aspect in this context is the assessment of the quality of the computed approximate solutions. In this paper we present a lower bound in terms of a linear program for this purpose. It is applicable to any pattern space. The only assumption we make is that the distance function used for the definition of generalized median is a metric. We will prove the optimality of the lower bound, i.e. it will be shown that no better one exists when considering all possible instances of generalized median problems. An experimental verification in the domain of strings and graphs shows the tightness, and thus the usefulness, of the proposed lower bound.