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Title: Improving the performance of the lip identification through the use of shape correction
Authors: Travieso González, Carlos Manuel 
Ravelo García, Antonio Gabriel 
Alonso Hernández, Jesús Bernardino 
Canino Rodríguez, José Miguel 
Dutta, Malay Kishore
UNESCO Clasification: Investigación
Keywords: Lip-based biometrics
Image processing
Pattern recognition
Automatic identification
Artificial intelligence
Issue Date: 2019
Journal: Applied Intelligence 
Abstract: This work presents automatic identification and verification approaches based on lip biometrics, using a static lip shape and applying a lip correction preprocessing, transforming data from Hidden Markov Model and being classified by Support Vector Machines. The classification system is conclusive for the identification of a person by the shape of the lips, even if the person presents soft facial emotions. Moreover the use of static lips shape has been revealed as a good option for security applications. The experiments have been carried out with two public datasets. One dataset was used to model and validate the approach, and the other dataset has been used to test the model blindly. The accuracy is up to 100% and 99.76% for GDPS-ULPGC and RaFD datasets respectively, using two training samples under a hold-out validation. Based on the results we can conclude that the system is very robust and stable with the highest classification capacity and minimal computation complexity.
ISSN: 0924-669X
DOI: 10.1007/s10489-018-1352-6
Source: Applied Intelligence [ISSN 0924-669X], v. 49 (5), p. 1823-1840
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