New Distance Measures Applied to Marble Classification

  • J. Caldas Pinto
  • J. M. Sousa
  • H. Alexandre
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2905)


Automatic marble classification based on their visual appearance is an important industrial issue, but due to the presence of randomly distributed high number of different colors and its subjective evaluation by human experts, the problem remains unsolved. In this paper, several new measures based on similarity tables built by human experts are introduced. They are used to improve the behavior of some clustering algorithms and to quantitatively characterize the results, increasing the correspondence of the measures to the visual appearance of the results. The obtained results show the effectiveness of the proposed methods.


Genetic Algorithm Cluster Algorithm Simulated Annealing Similarity Score Fuzzy Cluster 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2003

Authors and Affiliations

  • J. Caldas Pinto
    • 1
  • J. M. Sousa
    • 1
  • H. Alexandre
    • 1
  1. 1.Instituto Superior Técnico, Dept. of Mechanical Engineering, GCAR/IDMECTechnical University of LisbonLisbonPortugal

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