The Experts below are selected from a list of 141 Experts worldwide ranked by ideXlab platform

Stefano Tubaro - One of the best experts on this subject based on the ideXlab platform.

  • Video phylogeny tree reconstruction using aging measures
    2017 25th European Signal Processing Conference (EUSIPCO), 2017
    Co-Authors: Simone Milani, Paolo Bestagini, Stefano Tubaro
    Abstract:

    The increasing diffusion of user-friendly editing software and online media sharing platforms has brought forth a growing on-line availability of near-duplicate (ND) videos. The need of authenticating these contents and tracing back their history has led to the investigation of Forensic algorithms for the reconstruction of the video phylogeny tree (VPT), i.e., an acyclic directed graph summarizing video genealogical relationships. Unfortunately, state-of-the-art solutions for VPT reconstruction suffer from strong computational requirements. In this paper, we propose a processing age measure based on video DCT coefficients and motion vectors statistics, which enables to provide preliminary information about possible video parent-child relationship. The use of processing age allows a Forensic Analyst to blindly select a smaller amount of significant video pairs to be compared for VPT reconstruction. This solution grants computational complexity reduction to the overall VPT reconstruction pipeline.

  • video recapture detection based on ghosting artifact analysis
    International Conference on Image Processing, 2013
    Co-Authors: Paolo Bestagini, Marco Visentiniscarzanella, Marco Tagliasacchi, Pier Luigi Dragotti, Stefano Tubaro
    Abstract:

    Video Forensics is becoming a popular field of research and an increasing number of Forensic techniques have been proposed in the last few years. However, a simple yet effective method to fool many detectors consists in recapturing a video sequence with a camcorder. For this reason being able to detect video recapture is a topic of interest for a Forensic Analyst. In this paper, we first characterize the video recapture model, focusing on the common scenario of a sequence recaptured from a LCD monitor using a digital camcorder, then we propose a recapture detector for this case. The detector is based on the analysis of a characteristic ghosting artifact left by the recapture process. The presented algorithm is finally validated by means of tests on original and recaptured sequences. These tests prove that the algorithm achieves high accuracy results.

  • Revealing the traces of jpeg compression anti-Forensics,” Information Forensics and Security
    2013
    Co-Authors: Marco Tagliasacchi, Stefano Tubaro
    Abstract:

    Abstract—Due to the lossy nature of transform coding, JPEG introduces characteristic traces in the compressed images. A Forensic Analyst might reveal these traces by analyzing the his-togram of discrete cosine transform (DCT) coefficients and exploit them to identify local tampering, copy-move forgery, etc. At the same time, it has been recently shown that a knowledgeable adversary can possibly conceal the traces of JPEG compression, by adding a dithering noise signal in the DCT domain, in order to restore the histogram of the original image. In this paper, we study the processing chain that arises in the case of JPEG compression anti-Forensics. We take the perspective of the Forensic Analyst, and we show how it is possible to counter the aforementioned anti-Forensic method revealing the traces of JPEG compression, regardless of the quantization matrix being used. Tests on a large image dataset demonstrated that the proposed detector was able to achieve an average accuracy equal to 93%, rising above 99% when excluding the case of nearly lossless JPEG compression. Index Terms—Anti-Forensics, digital image Forensics, JPEG compression

S. Tubaro - One of the best experts on this subject based on the ideXlab platform.

  • VIDEO RECAPTURE DETECTION BASED ON GHOSTING ARTIFACT ANALYSIS
    2014
    Co-Authors: Paolo Bestagini, Pier Luigi Dragotti, M. Tagliasacchi, M. Visentini-scarzanella, S. Tubaro
    Abstract:

    Video Forensics is becoming a popular field of research and an increasing number of Forensic techniques have been proposed in the last few years. However, a simple yet effective method to fool many detectors consists in recapturing a video sequence with a camcorder. For this reason being able to detect video recapture is a topic of interest for a Forensic Analyst. In this paper, we first characterize the video recapture model, focusing on the common scenario of a sequence recaptured from a LCD monitor using a digital camcorder, then we propose a recapture detector for this case. The detector is based on the analysis of a characteristic ghosting artifact left by the recapture process. The presented algorithm is finally validated by means of tests on original and recaptured sequences. These tests prove that the algorithm achieves high accuracy results. Index Terms — video Forensics, recapturing, ghosting 1

  • Revealing the trace of JPEG Compression Anti-Forensics
    'Institute of Electrical and Electronics Engineers (IEEE)', 2013
    Co-Authors: G. Valenzise, M. Tagliasacchi, S. Tubaro
    Abstract:

    Due to the lossy nature of transform coding, JPEG introduces characteristic traces in the compressed images. A Forensic Analyst might reveal these traces by analyzing the histogram of discrete cosine transform (DCT) coefficients and exploit them to identify local tampering, copy-move forgery, etc. At the same time, it has been recently shown that a knowledgeable adversary can possibly conceal the traces of JPEG compression, by adding a dithering noise signal in the DCT domain, in order to restore the histogram of the original image. In this paper, we study the processing chain that arises in the case of JPEG compression anti-Forensics. We take the perspective of the Forensic Analyst, and we show how it is possible to counter the aforementioned anti-Forensic method revealing the traces of JPEG compression, regardless of the quantization matrix being used. Tests on a large image dataset demonstrated that the proposed detector was able to achieve an average accuracy equal to 93%, rising above 99% when excluding the case of nearly lossless JPEG compression

Paolo Bestagini - One of the best experts on this subject based on the ideXlab platform.

  • Video phylogeny tree reconstruction using aging measures
    2017 25th European Signal Processing Conference (EUSIPCO), 2017
    Co-Authors: Simone Milani, Paolo Bestagini, Stefano Tubaro
    Abstract:

    The increasing diffusion of user-friendly editing software and online media sharing platforms has brought forth a growing on-line availability of near-duplicate (ND) videos. The need of authenticating these contents and tracing back their history has led to the investigation of Forensic algorithms for the reconstruction of the video phylogeny tree (VPT), i.e., an acyclic directed graph summarizing video genealogical relationships. Unfortunately, state-of-the-art solutions for VPT reconstruction suffer from strong computational requirements. In this paper, we propose a processing age measure based on video DCT coefficients and motion vectors statistics, which enables to provide preliminary information about possible video parent-child relationship. The use of processing age allows a Forensic Analyst to blindly select a smaller amount of significant video pairs to be compared for VPT reconstruction. This solution grants computational complexity reduction to the overall VPT reconstruction pipeline.

  • VIDEO RECAPTURE DETECTION BASED ON GHOSTING ARTIFACT ANALYSIS
    2014
    Co-Authors: Paolo Bestagini, Pier Luigi Dragotti, M. Tagliasacchi, M. Visentini-scarzanella, S. Tubaro
    Abstract:

    Video Forensics is becoming a popular field of research and an increasing number of Forensic techniques have been proposed in the last few years. However, a simple yet effective method to fool many detectors consists in recapturing a video sequence with a camcorder. For this reason being able to detect video recapture is a topic of interest for a Forensic Analyst. In this paper, we first characterize the video recapture model, focusing on the common scenario of a sequence recaptured from a LCD monitor using a digital camcorder, then we propose a recapture detector for this case. The detector is based on the analysis of a characteristic ghosting artifact left by the recapture process. The presented algorithm is finally validated by means of tests on original and recaptured sequences. These tests prove that the algorithm achieves high accuracy results. Index Terms — video Forensics, recapturing, ghosting 1

  • video recapture detection based on ghosting artifact analysis
    International Conference on Image Processing, 2013
    Co-Authors: Paolo Bestagini, Marco Visentiniscarzanella, Marco Tagliasacchi, Pier Luigi Dragotti, Stefano Tubaro
    Abstract:

    Video Forensics is becoming a popular field of research and an increasing number of Forensic techniques have been proposed in the last few years. However, a simple yet effective method to fool many detectors consists in recapturing a video sequence with a camcorder. For this reason being able to detect video recapture is a topic of interest for a Forensic Analyst. In this paper, we first characterize the video recapture model, focusing on the common scenario of a sequence recaptured from a LCD monitor using a digital camcorder, then we propose a recapture detector for this case. The detector is based on the analysis of a characteristic ghosting artifact left by the recapture process. The presented algorithm is finally validated by means of tests on original and recaptured sequences. These tests prove that the algorithm achieves high accuracy results.

Marco Tagliasacchi - One of the best experts on this subject based on the ideXlab platform.

  • video recapture detection based on ghosting artifact analysis
    International Conference on Image Processing, 2013
    Co-Authors: Paolo Bestagini, Marco Visentiniscarzanella, Marco Tagliasacchi, Pier Luigi Dragotti, Stefano Tubaro
    Abstract:

    Video Forensics is becoming a popular field of research and an increasing number of Forensic techniques have been proposed in the last few years. However, a simple yet effective method to fool many detectors consists in recapturing a video sequence with a camcorder. For this reason being able to detect video recapture is a topic of interest for a Forensic Analyst. In this paper, we first characterize the video recapture model, focusing on the common scenario of a sequence recaptured from a LCD monitor using a digital camcorder, then we propose a recapture detector for this case. The detector is based on the analysis of a characteristic ghosting artifact left by the recapture process. The presented algorithm is finally validated by means of tests on original and recaptured sequences. These tests prove that the algorithm achieves high accuracy results.

  • Revealing the traces of jpeg compression anti-Forensics,” Information Forensics and Security
    2013
    Co-Authors: Marco Tagliasacchi, Stefano Tubaro
    Abstract:

    Abstract—Due to the lossy nature of transform coding, JPEG introduces characteristic traces in the compressed images. A Forensic Analyst might reveal these traces by analyzing the his-togram of discrete cosine transform (DCT) coefficients and exploit them to identify local tampering, copy-move forgery, etc. At the same time, it has been recently shown that a knowledgeable adversary can possibly conceal the traces of JPEG compression, by adding a dithering noise signal in the DCT domain, in order to restore the histogram of the original image. In this paper, we study the processing chain that arises in the case of JPEG compression anti-Forensics. We take the perspective of the Forensic Analyst, and we show how it is possible to counter the aforementioned anti-Forensic method revealing the traces of JPEG compression, regardless of the quantization matrix being used. Tests on a large image dataset demonstrated that the proposed detector was able to achieve an average accuracy equal to 93%, rising above 99% when excluding the case of nearly lossless JPEG compression. Index Terms—Anti-Forensics, digital image Forensics, JPEG compression

M. Tagliasacchi - One of the best experts on this subject based on the ideXlab platform.

  • VIDEO RECAPTURE DETECTION BASED ON GHOSTING ARTIFACT ANALYSIS
    2014
    Co-Authors: Paolo Bestagini, Pier Luigi Dragotti, M. Tagliasacchi, M. Visentini-scarzanella, S. Tubaro
    Abstract:

    Video Forensics is becoming a popular field of research and an increasing number of Forensic techniques have been proposed in the last few years. However, a simple yet effective method to fool many detectors consists in recapturing a video sequence with a camcorder. For this reason being able to detect video recapture is a topic of interest for a Forensic Analyst. In this paper, we first characterize the video recapture model, focusing on the common scenario of a sequence recaptured from a LCD monitor using a digital camcorder, then we propose a recapture detector for this case. The detector is based on the analysis of a characteristic ghosting artifact left by the recapture process. The presented algorithm is finally validated by means of tests on original and recaptured sequences. These tests prove that the algorithm achieves high accuracy results. Index Terms — video Forensics, recapturing, ghosting 1

  • Revealing the trace of JPEG Compression Anti-Forensics
    'Institute of Electrical and Electronics Engineers (IEEE)', 2013
    Co-Authors: G. Valenzise, M. Tagliasacchi, S. Tubaro
    Abstract:

    Due to the lossy nature of transform coding, JPEG introduces characteristic traces in the compressed images. A Forensic Analyst might reveal these traces by analyzing the histogram of discrete cosine transform (DCT) coefficients and exploit them to identify local tampering, copy-move forgery, etc. At the same time, it has been recently shown that a knowledgeable adversary can possibly conceal the traces of JPEG compression, by adding a dithering noise signal in the DCT domain, in order to restore the histogram of the original image. In this paper, we study the processing chain that arises in the case of JPEG compression anti-Forensics. We take the perspective of the Forensic Analyst, and we show how it is possible to counter the aforementioned anti-Forensic method revealing the traces of JPEG compression, regardless of the quantization matrix being used. Tests on a large image dataset demonstrated that the proposed detector was able to achieve an average accuracy equal to 93%, rising above 99% when excluding the case of nearly lossless JPEG compression