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Annalisa Franco

Assistant professor

Department of Computer Science and Engineering

Academic discipline: ING-INF/05 Information Processing Systems


  • Biometric systems
  • Face detection and recognition
  • Image databases

Biometric systems

A biometric system is an automated method of identifying an individual based on his/her physiological (fingerprint, face, hand, retina, iris, ...) or behavioral (voice, handwriting, keystroke style, ...) characteristics. Many different biometric characteristics can be exploited, and each biometric trait presents peculiar characteristics in terms of individuality, acquisition procedure and degree of acceptance. In the last few years, the interest in biometric systems has grown significantly: academic research groups and companies have spent a lot of resources to study highly accurate personal identification systems. In fact, automated identification systems can be very useful in several applications (e.g., physical access control, time and attendance, automatic surveillance, network security, online transactions, …).

Among the possible biometric characteristics, face represents one of the more interesting since the acquisition procedure in not invasive (it does not need to use particular devices or scanners such as those adopted for fingerprint acquisition) and does not require the user cooperation. Although the recognition accuracy of this biometric is not as high as others (e.g. fingerprints), there are many fields where face recognition find its ideal application. An example is video-surveillance in environments where there is a high risk of terrorist acts (airports, stations, embassies): the use of a face recognition system could raise timely alarms when dangerous individuals are identified; analogously, face-based anti-robbery protection systems could be installed in banks and post offices, to alert about the presence of known criminals. In some applications, finally, face is the only biometric characteristic that can be employed to guarantee that the user of a given system (e.g. a computer or a cashier's window) continues, during the whole work session, to be the same who initially logged in.

The main issues addressed by the research staff are face detection and recognition in complex backgrounds. Moreover some recognition techniques based on the joint use of three-dimensional face models and two-dimensional images are studied to improve the recognition accuracy (thanks to the 3D information), retaining at the same time the efficiency in the recognition stage typical of 2D-based approaches.


Image databases

An image database (IDB) is a system in which a large amount of image data and their related i nformation are stored and managed.

Major objectives of an IDB are efficient storage, powerful retrieval capability, flexible data manipulation, efficient indexing. The research in this field is focused on two main issues: efficacy of similarity searches and efficiency in data retrieval in image databases.

As to similarity searches in image databases, some relevance feedback techniques are studied to improve the retrieval results. Relevance feedback approaches are based on a continuous interaction with the user that, providing a judgment on the result obtained for a query, allows the system to gradually adapt its similarity metric to better capture the user perception.

The research activity is also focused on the study of indexing techniques for multidimensional data. In particular indexing techniques have been designed specifically to deal with high dimensional data that present peculiar characteristics that make them very difficult to manage.

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