Down syndrome recognition using local binary patterns and statistical evaluation of the system

Authors:
Kurt Burçin;Nabiyev V. Vasif
Affiliations:
Department of Computer Engineering, Karadeniz Technical University, Trabzon, Turkey;Department of Computer Engineering, Karadeniz Technical University, Trabzon, Turkey
Venue:
Expert Systems with Applications: An International Journal
Year:
2011

Citing 1
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Abstract

Down syndrome has a private facial view, thus it can be recognized by using facial features. But this is a very challenging problem when the similarity between the faces of people with Down syndrome and not Down syndrome people are considered. Therefore, we used the local binary pattern (LBP) approach for feature extraction which is a very effective feature descriptor. For classification Euclidean distance and Changed Manhattan distance methods are used. In this way, we improved an efficient system to recognize Down syndrome.