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

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) approa...

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Bibliographic Details
Published inExpert systems with applications Vol. 38; no. 7; pp. 8690 - 8695
Main Authors Burçin, Kurt, Vasif, Nabiyev V.
Format Journal Article
LanguageEnglish
Published Elsevier Ltd 01.07.2011
Subjects
Binary systems
Classification
Down syndrome recognition
Expert systems
Facial
Feature extraction
Local binary pattern
Recognition
Similarity
Down syndrome recognition
Local binary pattern
Feature extraction
Classification
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Summary: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.
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ISSN:0957-4174
1873-6793
DOI:10.1016/j.eswa.2011.01.076