The present paper proposes a blind multi-bit watermarking method for High Dynamic Range (HDR) images. The proposed
approach is designed in order to guarantee the watermark imperceptibility both in the HDR marked image and in its Low
Dynamic Range (LDR) counterpart, being thus robust against significant non-linear distortions such as those performed
by tone-mapping operators (TMOs). In order to do so, the wavelet transform of the Just Noticeable Difference (JND)-
scaled space of the original HDR image is employed as embedding domain. Moreover, a visual mask taking into account
specific aspects of the Human Visual System (HVS) is exploited to improve the quality of the resulting watermarked image.
Specifically, bilateral filtering is used to locate information on the detail part of the HDR image, where the watermark
should be preferably embedded. A contrast sensitivity function is also employed to modulate the watermark intensity
in each wavelet decomposition subband according to its scale and orientation. An extensive set of experimental results
testifies the effectiveness of the proposed scheme in embedding multi-bit watermarks into HDR images without affecting
the visual quality of the original image, while being robust against TMOs.
In this paper an adaptive feature-based approach to on-line signature verification is presented. Cryptographic
techniques are employed to protect the extracted templates thus making impossible to derive the original biometric
data from the stored information, as well as to generate multiple templates from the same original biometrics.
Our approach allows to obtain, together with protection, also template cancelability thus guaranteeing user's
privacy. The proposed authentication scheme is able to automatically adjust its parameters to the variability of
each user's signature, thus obtaining a user adaptive system with enhanced performances with respect to a nonadaptive
one. Experimental results show the effectiveness of our approach. Also the effects on the recognition performances when using the pen inclination features are investigated.
Biometrics is rapidly becoming the principal technology
for automatic people authentication. The main advantage in using
biometrics over traditional recognition approaches relies in the difficulty
of losing, stealing, or copying individual behavioral or physical
traits. The major weakness of biometrics-based systems relies in
their security: in order to avoid data stealing or corruption, storing
raw biometric data is not advised. The same problem occurs when
biometric templates are employed, since they can be used to recover
the original biometric data. We employ cryptographic techniques
to protect dynamic signature features, making it impossible
to derive the original biometrics from the stored templates, while
maintaining good recognition performances. Together with protection,
we also guarantee template cancellability and renewability.
Moreover, the proposed authentication scheme is tailored to the signature
variability of each user, thus obtaining a user adaptive system
with enhanced performances with respect to a nonadaptive
one. Experimental results show the effectiveness of our approach
when compared to both traditional nonsecure classifiers and other,
already proposed protection schemes.
In this paper we propose a signature-based biometric system, where watermarking is applied to signature images in order to hide and keep secret some signature features in a static representation of the signature itself. Being a behavioral biometric, signatures are intrinsically different from other commonly used biometric data, possessing dynamic properties which can not be extracted from a
single signature image. The marked images can be used for user authentication, letting their static characteristics being analyzed by automatic algorithms or security attendants. When a higher security is needed, the embedded features can be extracted and used, thus realizing a multi-level decision procedure. The proposed watermarking techniques are tailored to images with sharpened edges, just like a signature picture. In order to obtain a robust method,
able to hide relevant data while keeping intact the original structure of the host, the mark is embedded as close as possible to the lines that constitute the signature, using the properties of the Radon transform. An extensive set of experimental results, obtained varying the system's parameters and concerning both the mark
extraction and the verification performances, show the effectiveness
of our approach.
In the last decade a lot of efforts have been devoted to the development of biometrics-based authentication
systems. In this paper we propose a signature-based biometric authentication system, where watermarking
techniques are used to embed some dynamic signature features in a static representation of the signature itself,
stored either in a centralized database or in a smartcard. The user authentication can be performed either by using
some static features extracted from the acquired signature or by using both the aforementioned static features
together with the dynamic features embedded in the enrollment stage. A multi-level authentication system,
which is capable to provide various degree of security, is thus obtained. The proposed watermarking techniques
are tailored to images with sharp edges, like a signature picture, in order to obtain a robust embedding method
while keeping intact the original structure of the host signal. Experimental results show the two different levels
of security which can be reached when either static features or both static and dynamic features are employed in the authentication process.
The most emerging technology for people identification and authentication is biometrics. In contrast with
traditional recognition approaches, biometric authentication relies on who a person is or what a person does,
being based on strictly personal traits, much more difficult to be forgotten, lost, stolen, copied or forged than
traditional data. In this paper, we focus on two vulnerable points of biometric systems: the database where the
templates are stored and the communication channel between the stored templates and the matcher. Specifically,
we propose a method, based on user adaptive error correction codes, to achieve securitization and cancelability of
the stored templates applied to dynamic signature features. More in detail, the employed error correction code is
tailored to the intra-class variability of each user's signature features. This leads to an enhancement of the system
performance expressed in terms of false acceptance rate. Moreover, in order to avoid corruption or interception
of the stored templates in the transmission channels, we propose a scheme based on threshold cryptography:
the distribution of the certificate authority functionality among a number of nodes provides distributed, fault-tolerant,
and hierarchical key management services. Experimental results show the effectiveness of our approach,
when compared to traditional non-secure correlation-based classifiers.
In this paper we propose a new approach for the synthesis of natural video textures. After generalizing the bidimensional extended self-similar (ESS) model to the three dimensional (3D) case we want to generate samples of 3D-ESS fields on a discrete grid. The video texture is modeled according to the 3D-ESS model. The autocorrelation functions (ACFs) of the increments of the original video texture, at different spatial and temporal scales, are estimated according to the 3D-ESS model. A synthetic 3D-ESS field, whose increments have the same ACFs of the corresponding ones of the given prototype, is generated using the incremental Fourier synthesis algorithm.