Fabrizio Guerrini

Bio: Fabrizio Guerrini is an academic researcher from University of Brescia. The author has contributed to research in topics: Digital watermarking & Symmetry (geometry). The author has an hindex of 7, co-authored 34 publications receiving 178 citations. Previous affiliations of Fabrizio Guerrini include Teesside University.

High Dynamic Range Image Watermarking Robust Against Tone-Mapping Operators

Abstract: High dynamic range (HDR) images represent the future format for digital images since they allow accurate rendering of a wider range of luminance values. However, today special types of preprocessing, collectively known as tone-mapping (TM) operators, are needed to adapt HDR images to currently existing displays. Tone-mapped images, although of reduced dynamic range, have nonetheless high quality and hence retain some commercial value. In this paper, we propose a solution to the problem of HDR image watermarking, e.g., for copyright embedding, that should survive TM. Therefore, the requirements imposed on the watermark encompass imperceptibility, a certain degree of security, and robustness to TM operators. The proposed watermarking system belongs to the blind, detectable category; it is based on the quantization index modulation (QIM) paradigm and employs higher order statistics as a feature. Experimental analysis shows positive results and demonstrates the system effectiveness with current state-of-art TM algorithms.

Method and system for generating an alternative audible, visual and/or textual data based upon an original audible, visual and/or textual data

Abstract: A computer implemented method and system for generating an alternative audible, visual and/or textual data based upon an original audible, visual and/or textual data comprising the step of inputting to a processor original audible, visual and/or textual data having an original plot, extracting a plurality of basic segments from the original audible, visual and/or textual data, defining a vocabulary of intermediate-level semantic concepts based on the plurality of basic segments and/or the original plot, inputting to the processor at least an alternative plot based upon the original plot, modifying the alternative plot in terms of the vocabulary of intermediate-level semantic concepts for generating a modified alternative plot, and modifying the plurality of basic segments of the original audible, visual and/or textual data in terms of said vocabulary of intermediate-level semantic concepts for generating a modified plurality of basic segments.

Generating story variants with constrained video recombination

Abstract: We present a novel approach to the automatic generation of filmic variants within an implemented Video-Based Storytelling (VBS) system that successfully integrates video segmentation with stochastically controlled re-ordering techniques and narrative generation via AI planning. We have introduced flexibility into the video recombination process by sequencing video shots in a way that maintains local video consistency and this is combined with exploitation of shot polysemy to enable shot reuse in a range of valid semantic contexts. Results of evaluations on output narratives using a shared set of video data show consistency in terms of local video sequences and global causality with no loss of generative power.

Representation of signals by local symmetry decomposition

Abstract: In this paper we propose a segmentation of finite support sequences based on the even/odd decomposition of a signal. The objective is to ind a more compact representation of information. To this aim, the paper starts to generalize the even/odd decomposition by concentrating the energy on either the even or the odd part by optimally placing the centre of symmetry. Local symmetry intervals are thus located. The sequence segmentation is further processed by applying an iterative growth on the candidate segments to remove any overlapping portions. Experimental results show that the set of segments can be more eficiently compressed with respect to the DCT transformation of the entire sequence, which corresponds to the near optimal KLT transform of the data chosen for the experiment.

A new video authentication template based on bubble random sampling

Abstract: The rapid growth of digital video distribution has highlighted new important issues in digital rights management, as well as in other important applications such as video authentication. Digital watermarking offers a promising solution against piracy and it is therefore a very active area of research. However, robustness to video manipulations, either malicious or not, is a demanding task because there are many different types of possible attacks that can be envisioned. Among these, geometric and temporal distortions play the major roles. The countermeasures against these specific attacks are still an open challenge. In this paper we propose the use of a video authentication template based on bubble random sampling. The authentication template is introduced in order to ensure temporal synchronization and to prevent content tampering. The simulation results are encouraging and this approach is therefore worth further development efforts.

The Self-Organizing Map

Abstract: An overview of the self-organizing map algorithm, on which the papers in this issue are based, is presented in this article.

The Merchant of Veniceの言葉について

Abstract: Act IV, sc. 1 (line 264) ANTONIO But little: I am arm'd and well prepared. Give me your hand, Bassanio: fare you well! Grieve not that I am fallen to this for you; For herein Fortune shows herself more kind Than is her custom: it is still her use To let the wretched man outlive his wealth, To view with hollow eye and wrinkled brow An age of poverty; from which lingering penance Of such misery doth she cut me off. Commend me to your honourable wife: Tell her the process of Antonio's end; Say how I loved you, speak me fair in death; And, when the tale is told, bid her be judge Whether Bassanio had not once a love. Repent but you that you shall lose your friend, And he repents not that he pays your debt; For if the Jew do cut but deep enough, I'll pay it presently with all my heart.

Patchwork-based audio watermarking method robust to de-synchronization attacks

Abstract: This paper presents a patchwork-based audio watermarking method to resist de-synchronization attacks such as pitch-scaling, time-scaling, and jitter attacks. At the embedding stage, the watermarks are embedded into the host audio signal in the discrete cosine transform (DCT) domain. Then, a set of synchronization bits are implanted into the watermarked signal in the logarithmic DCT (LDCT) domain. At the decoding stage, we analyze the received audio signal in the LDCT domain to find the scaling factor imposed by an attack. Then, we modify the received signal to remove the scaling effect, together with the embedded synchronization bits. After that, watermarks are extracted from the modified signal. Simulation results show that at the embedding rate of 10 bps, the proposed method achieves 98.9% detection rate on average under the considered de-synchronization attacks. At the embedding rate of 16 bps, it can still obtain 94.7% detection rate on average. So, the proposed method is much more robust to de-synchronization attacks than other patchwork watermarking methods. Compared with the audio watermarking methods designed for tackling de-synchronization attacks, our method has much higher embedding capacity.

A Novel Data Hiding Algorithm for High Dynamic Range Images

Abstract: In this paper, we propose a novel data hiding algorithm for high dynamic range (HDR) images encoded by the OpenEXR file format. The proposed algorithm exploits each of three 10-bit mantissa fields as an embedding unit in order to conceal k bits of a secret message using an optimal base which produces the least pixel variation. An aggressive bit encoding and decomposition scheme is recommended, which offers a high probability to convey ( k + 1) bits without increasing the pixel variation caused by message concealment. In addition, we present a bit inversion embedding strategy to further increase the capacities when the probability of appearance of secret bit “1” is greater than 0.5. Furthermore, we introduce an adaptive data hiding approach for concealing more secret messages in pixels with low luminance, exploiting the features of the human visual system to achieve luminance-aware adaptive data hiding. The stego HDR images produced by our algorithm coincide with the HDR image file format, causing no suspicion from malicious eavesdroppers. The generated stego HDR images and their tone-mapped low dynamic range (LDR) images reveal no perceptual differences when subjected to quantitative testing by visual difference predictor. Our algorithm can resist steganalytic attacks from the HDR and LDR RS and SPAM steganalyzers. We present the first data hiding algorithm for OpenEXR HDR images offering a high embedding rate and producing high visual quality of the stego images. Our algorithm outperforms the current state-of-the-art works.