Evolutionary Algorithm for Dense Pixel Matching in Presence of Distortions

  • Ana Carolina dos-Santos-Paulino
  • Jean-Christophe Nebel
  • Francisco Flórez-RevueltaEmail author
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8602)


Dense pixel matching is an essential step required by many computer vision applications. While a large body of work has addressed quite successfully the rectified scenario, accurate pixel correspondence between an image and a distorted version remains very challenging. Exploiting an analogy between sequences of genetic material and images, we propose a novel genetics inspired algorithm where image variability is treated as the product of a set of image mutations. As a consequence, correspondence for each scanline of the initial image is formulated as the optimisation of a path in the second image minimising a fitness function penalising mutations. This optimisation is performed by a evolutionary algorithm which, in addition to provide fast convergence, implicitly ensures consistency between successive scanlines. Performance evaluation on locally and globally distorted images validates our bio-inspired approach.


Evolutionary algorithm Dense pixel matching Unrectified images Distorted images 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2014

Authors and Affiliations

  • Ana Carolina dos-Santos-Paulino
    • 1
  • Jean-Christophe Nebel
    • 2
  • Francisco Flórez-Revuelta
    • 2
    Email author
  1. 1.Télécom Physique StrasbourgUniversité de StrasbourgIllkirch-GraffenstadenFrance
  2. 2.Faculty of Science, Engineering and ComputingKingston UniversityKingston upon ThamesUK

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