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Explicit Modelling of Invariances in Bernoulli Mixtures for Binary Images

  • Verónica Romero
  • Adrià Giménez
  • Alfons Juan
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4477)

Abstract

Bernoulli mixture models have been recently proposed as simple yet powerful probabilistic models for binary images in which each image pattern is modelled by a different Bernoulli prototype (component). A possible limitation of these models, however, is that usual geometric transformations of image patterns are not explicitly modelled and, therefore, each natural transformation of an image pattern has to be independently modelled using a different, rigid prototype. In this work, we propose a simple technique to make these rigid prototypes more flexible by explicit modelling of invariances to translation, scaling and rotation. Results are reported on a task of handwritten Indian digits recognition.

Keywords

Binary Image Explicit Modelling Image Pattern Virtual Prototype Indian Digit 
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 Berlin Heidelberg 2007

Authors and Affiliations

  • Verónica Romero
    • 1
  • Adrià Giménez
    • 1
  • Alfons Juan
    • 1
  1. 1.Departament de Sistemes Informàtics i Computació, Universitat Politècnica de València, Camí de Vera s/n, 46022 València (Spain) 

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