SciELO - Scientific Electronic Library Online

 
vol.10 issue1Preliminary assessment of Random Indexing variants for Text Categorization in Online Learning ContextPerformance assessment of MOVMO metaheuristic on constrains test functions author indexsubject indexarticles search
Home Pagealphabetic serial listing  

Services on Demand

Article

Indicators

  • Have no cited articlesCited by SciELO

Related links

  • Have no similar articlesSimilars in SciELO

Share


Revista Cubana de Ciencias Informáticas

On-line version ISSN 2227-1899

Abstract

BECERRA-RIERA, Fabiola  and  MORALES-GONZALEZ, Annette. Detection and matching of facial marks in face images. Rev cuba cienc informat [online]. 2016, vol.10, n.1, pp. 172-181. ISSN 2227-1899.

ABSTRACT Soft biometrics traits (e.g.  gender, ethnicity, facial marks) are complementary information in face recognition. Although they are not fully distinctive by themselves, recent studies have proven that they can be combined with classical facial recognition techniques to increase the accuracy of the process. Facial marks, in particular, have proven useful in reducing the search for the identity of individuals, although they do not uniquely identify them. Facial marks based systems provide specific and more significant evidence about the similarity between faces. In this paper we propose the use of facial marks (e.g.   moles, freckles, warts) to improve the face recognition process.  To that end, we implemented an algorithm for automatic detection of facial marks and we proposed two matching algorithms: one based on Histograms of Oriented Gradients (HoG) to represent the marks and the other based on the intensities of the pixels contained in each mark bounding box. Experimental results based on a set of 530 images (265 subjects) with manually annotated facial marks, show that the combination of traditional face recognition techniques with facial marks, increases the accuracy of the process.

Keywords : Soft biometrics; facial marks; face recognition.

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

 

Creative Commons License All the contents of this journal, except where otherwise noted, is licensed under a Creative Commons Attribution License