SciELO - Scientific Electronic Library Online

 issue79Automatic segmentation of lizard spots using an active contour modelAn insight to the automatic categorization of speakers according to sex and its application to the detection of voice pathologies: A comparative study author indexsubject indexarticles search
Home Pagealphabetic serial listing  

Services on Demand



Related links

  • On index processCited by Google
  • Have no similar articlesSimilars in SciELO
  • On index processSimilars in Google


Revista Facultad de Ingeniería Universidad de Antioquia

Print version ISSN 0120-6230


GOMEZ-VILLA, Alexander; DIEZ-VALENCIA, Germán  and  SALAZAR-JIMENEZ, Augusto Enrique. A Markov random field image segmentation model for lizard spots. Antioquia [online]. 2016, n.79, pp.41-49. ISSN 0120-6230.

Animal identification as a method for fauna study and conservation can be implemented using phenotypic appearance features such as spots, stripes or morphology. This procedure has the advantage that it does not harm study subjects. The visual identification of the subjects must be performed by a trained professional, who may need to inspect hundreds or thousands of images, a time-consuming task. In this work, several classical segmentation and preprocessing techniques, such as threshold, adaptive threshold, histogram equalization, and saturation correction are analyzed. Instead of the classical segmentation approach, herein we propose a Markov random field segmentation model for spots, which we test under ideal, standard and challenging acquisition conditions. As study subject, the Diploglossus millepunctatus lizard is used. The proposed method achieved a maximum efficiency of 84.87%.

Keywords : Belief propagation; Markov network; Graph Cuts; animal biometrics; Markov random field; Diploglossus millepunctatus.

        · abstract in Spanish     · text in English     · English ( pdf )