Discovering Patterns With and Within Images

  • Osmar R. Zaïane
Part of the Multimedia Systems and Applications Series book series (MMSA, volume 22)


The process of knowledge discovery from data, also known as KDD, comprises steps such as gathering and consolidating data, pre-processing then selecting data, mining the selected data, then finally evaluating the discovered patterns for possible interpretation and use [28]. To be profitable and constructive, this nontrivial process, which includes the step of data mining, needs to extract implicit, previously unknown and potentially useful information from large data [28]. The knowledge extracted, or discovered, is usually in the form of patterns such as data characterization, classes, clusters, frequent sequences, data models, rules such as association rules, etc. [15]. While knowledge discovery and data mining are typically used on corporate data for business intelligence, or on scientific data such as with bio-informatics, with the advances in multimedia data acquisition and storage techniques, the need for automatically discovering patterns from large image and video collections is becoming more and more relevant in many applications.


Data Mining Association Rule Knowledge Discovery Visual Feature Image Query 
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 Science+Business Media New York 2003

Authors and Affiliations

  • Osmar R. Zaïane
    • 1
  1. 1.University of AlbertaCanada

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