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Título
A Small Look at the Ear Recognition Process using a Hybrid Approach
Autor(es)
Materia
Computer Science
Fecha de publicación
2016
Editor
Elsevier
Citación
Journal of Applied Logic. Volumen 17, pp. 4–13. Elsevier.
Resumen
The purpose of this document is to offer a combined approach in biometric analysis field, integrating some of the most known techniques using ears to recognize people. This study uses Hausdorff distance as a pre-processing stage adding sturdiness to increase the performance filtering for the subjects to use it in the testing process. Also includes the Image Ray Transform (IRT) and the Haar based classifier for the detection step. Then, the system computes Speeded Up Robust Features (SURF) and Linear Discriminant Analysis (LDA) as an input of two neural networks to recognize a person by the patterns of its ear. To show the applied theory experimental results, the above algorithms have been implemented using Microsoft C#. The investigation results showed robustness improving the ear recognition process.
URI
ISSN
1570-8683
Colecciones
- BISITE. Artículos [289]
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