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Standard edge detectors react to all local luminance changes, irrespective of whether they are due to the contours of the objects represented in a scene or due to natural textures like grass, foliage, water, and so forth. Moreover, edges due to texture are often stronger than edges due to object contours. This implies that further processing is needed to discriminate object contours from texture edges. In this paper, we propose a biologically motivated multiresolution contour detection method using Bayesian denoising and a surround inhibition technique. Specifically, the proposed approach deploys computation of the gradient at different resolutions, followed by Bayesian denoising of the edge image. Then, a biologically motivated surround inhibition step is applied in order to suppress edges that are due to texture. We propose an improvement of the surround suppression used in previous works. Finally, a contour-oriented binarization algorithm is used, relying on the observation that object contours lead to long connected components rather than to short rods obtained from textures. Experimental results show that our contour detection method outperforms standard edge detectors as well as other methods that deploy inhibition. research activity has been focused mainly on information theory, signal theory, and signal and image processing and their applications to both telecommunications systems and remote sensing.

A new approach for keystroke-based authentication when using a cellular phone keypad as input device is presented. In the proposed method, users are authenticated using keystroke dynamics acquired when typing fixed alphabetic strings on a mobile phone keypad. The employed statistical classifier is able to perform user verification with an average equal error rate of about 13%. The obtained experimental results suggest that, when using mobile devices, a strong secure authentication scheme cannot rely on the sole keystroke dynamics, which however can be a module of a more complex system including, as basic security, a password-based protocol eventually hardened by keystroke analysis.

A dictionary of complex waveforms suited for multiresolution analysis and individually steerable by multiplication by a complex factor is presented. It is based on circular harmonic wavelets (CHW) and is useful for pattern analysis under rotations. The main theoretical aspects of CHWs are illustrated, and an example of application to motion estimation is provided

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Abstract-This paper presents a novel method to blindly estimate the quality of a multimedia communication link by means of an unconventional use of digital fragile watermarking. Data hiding by digital watermarking is usually employed for multimedia copyright protection, authenticity verification, or similar purposes. However, watermarking is here adopted as a technique to provide a blind measure of the quality of service in multimedia communications. Specifically, a fragile watermark is hidden in an MPEG-like host data video transport stream using a spread-spectrum approach. Like a tracing signal, the watermark tracks the data, where it is embedded, since both the watermark and the host data follow the same communication link. The estimation of the tracing watermark allows dynamically evaluating the effective quality of the provided video services. This depends on the whole physical layer, including the employed video co/decoder. The performed method is based on the evaluation of the mean-square-error between the estimated and the actual watermarks. The proposed technique has been designed for application to wireless multimedia communication systems. According to the results obtained, the sensitivity of the detected tracing watermark on the quality of service (QoS) indices provides for some useful capabilities for analyzing future mobile Universal Mobile Telecommunications System (UMTS) services.Index Terms-Multimedia communications, quality of service, UMTS services, video streaming, watermarking.

Recent years have seen the rapid spread of biometric technologies for automatic people recognition. However, security and privacy issues still represent the main obstacles for the deployment of biometric-based authentication systems. In this paper, we propose an approach, which we refer to as BioConvolving, that is able to guarantee security and renewability to biometric templates. Specifically, we introduce a set of noninvertible transformations, which can be applied to any biometrics whose template can be represented by a set of sequences, in order to generate multiple transformed versions of the template. Once the transformation is performed, retrieving the original data from the transformed template is computationally as hard as random guessing. As a proof of concept, the proposed approach is applied to an on-line signature recognition system, where a hidden Markov model-based matching strategy is employed. The performance of a protected on-line signature recognition system employing the proposed BioConvolving approach is evaluated, both in terms of authentication rates and renewability capacity, using the MCYT signature database. The reported extensive set of experiments shows that protected and renewable biometric templates can be properly generated and used for recognition, at the expense of a slight degradation in authentication performance

In this paper we discuss the feasibility of employing keystroke dynamics to perform user verification on mobile phones. Specifically, after having introduced a new statistical classifier, we analyze the discriminative capabilities of the features extracted from the acquired patterns, in order to determine which ones guarantee the best authentication performances. The effectiveness of using template selection techniques for keystroke verification is also investigated.The obtained experimental results indicate that the proposed method can be effectively employed to authenticate mobile phones users, even in operational contexts where the number of enrollment acquisition is kept low.