Curvelets for Contact-less Hand Biometrics under varied environmental conditions
| Autor: | Miguel Viana-Matesanz, Carmen Sanchez-Avila, Belen Rios-Sanchez |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2017 |
| Předmět: |
Biometrics
Computer science business.industry Feature extraction Robótica e Informática Industrial 020207 software engineering Pattern recognition 02 engineering and technology Euclidean distance Support vector machine Norm (mathematics) 0202 electrical engineering electronic engineering information engineering Curvelet 020201 artificial intelligence & image processing Artificial intelligence business Hand geometry Feature matching |
| Zdroj: | 2017 International Carnahan Conference On Security Technology (ICCST), ISSN 1071-6572, 2017 ICCST |
| Popis: | In this work, the Curvelet transform is proposed as a fairly new feature extraction method for palmprint recognition. Particularly, a multiscale analysis has been performed at four levels, assessing and combining the features extracted at each level in order to find those which better represent the palmprint. Feature matching has been conducted by means of Euclidean distance and Support Vector Machines (SVMs), and comparative results are provided. In addition, a multimodal approach involving the extracted palmprint features and hand geometry features has also been evaluated, obtaining an improvement of the results in relation to monomodal biometrics. Evaluations have been carried out following an evaluation protocol based on the definitions suggested by the ISO/IDE 19795 norm that allows for a fair comparison between the different methods. To this end, images coming from two different contact-less databases, which cover different capturing conditions, have been employed. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|