Part of the Undergraduate Topics in Computer Science book series (UTICS, volume 0)


Pattern recognition can be defined as the classification of data based on knowledge already gained or on statistical information extracted from patterns and/or their representations.

It has several important applications. Multimedia document recognition (MDR) and automatic medical diagnosis are two such applications. For example, in MDR we have to deal with a combination of text, audio and video data. The text data may be made up of alpha-numerical characters corresponding to one or more natural languages. The audio data could be in the form of speech or music. Similarly, the video data could be a single image or a sequence of images—for example, the face of a criminal, his fingerprint and signature could come in the form of a single image. It is also possible to have a sequence of images of the same individual moving in an airport in the form of a video clip.


Support Vector Machine Pattern Recognition Class Label Video Data Classification Rule 
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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  1. 1.
    Bishop, C. M. Neural Networks for Pattern Recognition. New Delhi: Oxford University Press. 2003.Google Scholar
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    Duda, R. O., P. E. Hart and D. G. Stork. Pattern Classification. JohnWiley and Sons. 2000.Google Scholar
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    Russell, S. and P. Norvig. Artificial Intelligence: A Modern Approach. Pearson India. 2003.Google Scholar
  4. 4.
    Tan, P. N., M. Steinbach, and V. Kumar. Introduction to Data Mining. Pearson India. 2007.Google Scholar

Copyright information

© Universities Press (India) Pvt. Ltd. 2011

Authors and Affiliations

  1. 1.Dept. of Computer Science and AutomationIndian Institute of ScienceBangaloreIndia

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