Biometrics technology relies on the physiological traits such as fingerprint, face, palmprint, and iris pattern, or behavioral traits, such as gait, signature, handwriting, and keystroke dynamics for assigning unique identities to the individuals. In spite of the huge demands on biometrics systems, there are still several challenges that need to be addressed in order to enhance the performance of any biometric system in terms of time and accuracy. This special session emphasizes the usage of the advanced signal processing techniques for addressing some biometrics related problems. Common signal processing techniques such as spatial and frequency domains filtering, Scale-Invariant Feature Transform, and Wavelets contribute very well to solve some biometrics problems, and hence the advanced signal processing techniques are expected to achieve better results when tackling biometrics related problems. The aim of this session is to attract researchers and practitioners from academia and industry, and provide a discussion environment in order to share their experiences of using advanced signal processing techniques for addressing the challenges in biometrics research area. Topics of interest include but are not limited to:
- Advanced signal processing techniques:
- Applications with biometric data:
Ali Ismail Awad, Al Azhar University, Egypt
Kensuke Baba, Kyushu University, Japan
Papers should be submitted electronically. For further details, please consult the conference paper submission web page. When you submit your paper, please select “SS-2: Signal Processing for Biometrics” from the “Topics” list in the submission page. All articles will undergo a rigorous review process. Accepted papers will be published in the conference memory stick and on the IEEE Xplore.