Introduction to the Special Issue on Recent Advances in Biometric Systems

W E ARE pleased to present 14 papers in this special issue devoted to recent advances in biometric systems. A total of 78 papers were submitted for consideration for the special issue. Those that appear in this special issue result from a careful review process and consideration of timing for the special issue. Other papers, which were originally submitted for consideration for the special issue, may be undergoing major revisions and resubmission and appear at a later time in a regular issue of this journal or possibly in some other journal. In particular, several submissions in the area of iris biometrics could not be considered for this special issue due to their experimental results being based primarily on the CASIA 1 iris image dataset [1]. Papers on a broad variety of topics were submitted to the special issue. The large active areas of biometrics such as face, fingerprint, voice, signature, and iris were naturally well represented in the submissions. Newer and smaller areas such as gait and ear biometrics were also represented. Even more unusual areas such as brain signal recordings and infrared imaging of hand vein patterns were also represented. The diversity of topics in the submitted papers is reflected to some degree in the accepted papers and is an indication of the broad and vibrant current nature of the field. Security and privacy issues in large biometrics systems have received relatively less attention in the past. We are indeed fortunate to have two excellent papers in this area, dealing with what are called “revocable” or “cancelable” biometrics. The first paper works in the context of face recognition and the second paper models forgery for behavioral biometrics. The paper “Cancelable Biometrics Realization With Multispace Random Projections” by Teoh and Yuang addresses both revocability and privacy of biometrics templates using a twofactor cancelable formulation. In the first step, the biometric data are distorted by transforming the raw biometric data into a fixed-length feature vector in a nonreversible but revocable manner. In the second step, the feature vector is projected onto a sequence of random subspaces derived from user-specific pseudorandom numbers (PRNs). This process is invertible, thus making the replacement of biometrics possible by replacement of the PRNs. The proposed method has been verified using the FERET face database [10].