Tesis doctoral de Xavier Font Aragones
Biometric recognition refers to the automatic identification of a person based on his or her anatomical characteristic or modality (i.E., Fingerprint, palmprint, face) or behavioural (i.E., Signature) characteristic. It is a fundamental key issue in any process concerned with security, shared resources, network transactions among many others. Arises as a fundamental problem widely known as recognition, and becomes a must step before permission is granted. It is supposed that protects key resources by only allowing those resources to be used by users that have been granted authority to use or to have access to them. Biometric systems can operate in verification mode, where the question to be solved is am i who i claim i am? Or in identification mode where the question is who am i? Scientific community has increased its efforts in order to improve performance of biometric systems. Depending on the application many solutions go in the way of working with several modalities or combining different classification methods. Since increasing modalities require some user inconvenience many of these approaches will never reach the market. For example working with iris, face and fingerprints requires some user effort in order to help acquisition. this thesis addresses hand-based biometric system in a thorough way. The main contributions are in the direction of a new multi-spectral hand-based image database and methods for performance improvement. The main contributions are: a) the first multi-spectral hand-based image database from both hand faces: palmar and dorsal. Biometric database are a precious commodity for research, mainly when it offers something new like visual (vis), near infrared (nir) and thermography (tir) images at a time. This database with a length of 100 users and 10 samples per user constitute a good starting point to check algorithms and hand suitability for recognition. b) in order to correctly deal with raw hand data, some image preprocessing steps are necessary. Three different segmentation phases are deployed to deal with vis, nir and tir images specifically. Some of the tough questions to address: overexposed images, ring fingers and the cuffs, cold finger and noise image. once image segmented, two different approaches are prepared to deal with the segmented data. These two approaches called: holistic and geometric define the main focus to extract the feature vector. These feature vectors can be used alone or can be combined in some way. Many questions can be stated: e.G. Which approach is better for recognition?, Can fingers alone obtain better performance than the whole hand? And is thermography hand information suitable for recognition due to its thermoregulation properties? a complete set of data ready to analyse, coming from the holistic and geometric approach have been designed and saved to test. Some innovative geometric approach related to curvature will be demonstrated. c) finally the biometric dispersion matcher (bdm) is used in order to explore how it works under different fusion schemes, as well as with different classification methods. It is the intention of this research to contrast what happen when using other methods close to bdm like linear discriminant analysis (lda). At this point, some interesting questions will be solved, e.G. By taking advantage of the finger segmentation (as five different modalities) to figure out if they can outperform what the whole hand data can teach us.
Datos académicos de la tesis doctoral «Visible, near infrared and thermal hand-based image biometric recognition.«
- Título de la tesis: Visible, near infrared and thermal hand-based image biometric recognition.
- Autor: Xavier Font Aragones
- Universidad: Politécnica de catalunya
- Fecha de lectura de la tesis: 30/05/2013
Dirección y tribunal
- Director de la tesis
- Marcos Faundez Zanuy
- Tribunal
- Presidente del tribunal: Miguel angel Ferrer ballester
- raúl Sánchez reíllo (vocal)
- (vocal)
- (vocal)