  In this paper we address the issues of using edge detection techniques on
facial images to produce cancellable biometric templates and a novel method for
template verification against tampering. With increasing use of biometrics,
there is a real threat for the conventional systems using face databases, which
store images of users in raw and unaltered form. If compromised not only it is
irrevocable, but can be misused for cross-matching across different databases.
So it is desirable to generate and store revocable templates for the same user
in different applications to prevent cross-matching and to enhance security,
while maintaining privacy and ethics. By comparing different edge detection
methods it has been observed that the edge detection based on the Roberts Cross
operator performs consistently well across multiple face datasets, in which the
face images have been taken under a variety of conditions. We have proposed a
novel scheme using hashing, for extra verification, in order to harden the
security of the stored biometric templates.
