Proposing the novelty classifier for face recognition
Rev. bras. eng. biomed
;
30(4): 301-311, Oct.-Dec. 2014. ilus, graf, tab
Artigo
em Inglês
| LILACS
| ID: lil-732829
ABSTRACT
INTRODUCTION:
Face recognition, one of the most explored themes in biometry, is used in a wide range of applications access control, forensic detection, surveillance and monitoring systems, and robotic and human machine interactions. In this paper, a new classifier is proposed for face recognition the novelty classifier.METHODS:
The performance of a novelty classifier is compared with the performance of the nearest neighbor classifier. The ORL face image database was used. Three methods were employed for characteristic extraction principal component analysis, bi-dimensional principal component analysis with dimension reduction in one dimension and bi-dimensional principal component analysis with dimension reduction in two directions.RESULTS:
In identification mode, the best recognition rate with the leave-one-out strategy is equal to 100%. In the verification mode, the best recognition rate was also 100%. For the half-half strategy, the best recognition rate in the identification mode is equal to 98.5%, and in the verification mode, 88%.CONCLUSION:
For face recognition, the novelty classifier performs comparable to the best results already published in the literature, which further confirms the novelty classifier as an important pattern recognition method in biometry.
Texto completo:
DisponíveL
Índice:
LILACS (Américas)
Tipo de estudo:
Estudo prognóstico
Idioma:
Inglês
Revista:
Rev. bras. eng. biomed
Assunto da revista:
Engenharia Biomédica
Ano de publicação:
2014
Tipo de documento:
Artigo
País de afiliação:
Brasil
Instituição/País de afiliação:
Universidade Federal do Amazonas - UFAM/BR
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