Pattern Recognition

Pattern Recognition Algorithms

Pattern Recognition can be defined as the classification of input signals in different classes depending on their characteristics. In order to achieve this task, it is necessary to separate those really significant properties from those that are irrelevant details for the classification. An example of this situation is the handwritten characters classification in the corresponding types of letters from images that are in general noisy (i.e., images that have stains or partial deletions). Other applications are teledetection, speech recognition, fingerprints recognition, biomedical signal recognition, etc.

There are two main approaches to Pattern Recognition:

  • geometric methods, in which the signal is described in terms of a set of characteristics (number of curves, number of holes, etc)
  • structural or syntactic methods, in which the signal is described in terms of the relationship between its components

Contact information:

Luisa Micó: mico@dlsi.ua.es

Our postal address is:
Departamento de Lenguajes y Sistemas Informaticos.
Universidad de Alicante.
E-03080 Alicante.
Spain.

GRFIA Departamento de Lenguajes y Sistemas inform´ticos Universidad de Alicante Valid XHTML 1.0 Transitional Valid CSS 2.1