866,342 research outputs found

    Image Watermaking With Biometric Data For Copyright Protection

    Full text link
    In this paper, we deal with the proof of ownership or legitimate usage of a digital content, such as an image, in order to tackle the illegitimate copy. The proposed scheme based on the combination of the watermark-ing and cancelable biometrics does not require a trusted third party, all the exchanges are between the provider and the customer. The use of cancelable biometrics permits to provide a privacy compliant proof of identity. We illustrate the robustness of this method against intentional and unintentional attacks of the watermarked content

    An Image Morphing Technique Based on Optimal Mass Preserving Mapping

    Get PDF
    ©2007 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or distribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE. This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder.DOI: 10.1109/TIP.2007.896637Image morphing, or image interpolation in the time domain, deals with the metamorphosis of one image into another. In this paper, a new class of image morphing algorithms is proposed based on the theory of optimal mass transport. The 2 mass moving energy functional is modified by adding an intensity penalizing term, in order to reduce the undesired double exposure effect. It is an intensity-based approach and, thus, is parameter free. The optimal warping function is computed using an iterative gradient descent approach. This proposed morphing method is also extended to doubly connected domains using a harmonic parameterization technique, along with finite-element methods

    Dynamic Denoising of Tracking Sequences

    Get PDF
    ©2008 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or distribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE. This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder.DOI: 10.1109/TIP.2008.920795In this paper, we describe an approach to the problem of simultaneously enhancing image sequences and tracking the objects of interest represented by the latter. The enhancement part of the algorithm is based on Bayesian wavelet denoising, which has been chosen due to its exceptional ability to incorporate diverse a priori information into the process of image recovery. In particular, we demonstrate that, in dynamic settings, useful statistical priors can come both from some reasonable assumptions on the properties of the image to be enhanced as well as from the images that have already been observed before the current scene. Using such priors forms the main contribution of the present paper which is the proposal of the dynamic denoising as a tool for simultaneously enhancing and tracking image sequences.Within the proposed framework, the previous observations of a dynamic scene are employed to enhance its present observation. The mechanism that allows the fusion of the information within successive image frames is Bayesian estimation, while transferring the useful information between the images is governed by a Kalman filter that is used for both prediction and estimation of the dynamics of tracked objects. Therefore, in this methodology, the processes of target tracking and image enhancement "collaborate" in an interlacing manner, rather than being applied separately. The dynamic denoising is demonstrated on several examples of SAR imagery. The results demonstrated in this paper indicate a number of advantages of the proposed dynamic denoising over "static" approaches, in which the tracking images are enhanced independently of each other

    We are experienced! Jimi Hendrix in historical perspective

    Get PDF
    This article reflects on the decision of the Paris Tribunal de Grande Instance concerning copyright protection for a photograph of Jimi Hendrix by Gered Mankowitz (Bowstir Limited and Gered Mankowitz v. Egotrade SARL (2015)) and subsequent critical comment about the case, by providing an historical perspective on originality and photographic copyright. In doing so, it uncovers previously untold details of the history of photographic copyright and the first statutory originality criterion: introduced by section 1 Fine Arts Copyright Act 18621 and subsequently considered in Graves’ Case. 2 It argues that, while the decision in Bowstir seems surprising today, the points that complicated the Court’s reasoning are familiar from the standpoint of copyright history. An historical perspective, therefore, enables us to engage more critically with these issues. In commenting on the decision, the article draws on significant original research to be fully published in a forthcoming book (Art and Modern Copyright: The Contested Image, CUP, forthcoming 2016/173) which, in excavating a variety of little known perspectives on artistic copyright, shows history to be a rich terrain of ideas about copyright and the objects that it regulates

    Golan v. Holder: Copyright in the Image of the First Amendment

    Get PDF
    Does copyright violate the First Amendment? Professor Melville Nimmer asked this question forty years ago, and then answered it by concluding that copyright itself is affirmatively speech protective. Despite ample reason to doubt Nimmer’s response, the Supreme Court has avoided an independent, thoughtful, plenary review of the question. Copyright has come to enjoy an all-but-categorical immunity to First Amendment constraints. Now, however, the Court faces a new challenge to its back-of-the-hand treatment of this vital conflict. In Golan v. Holder the Tenth Circuit considered legislation (enacted pursuant to the Berne Convention and TRIPS) “restoring” copyright protection to millions of foreign works previously thought to belong to the public domain. The Tenth Circuit upheld the legislation, but not without noting that it appeared to raise important First Amendment concerns. The Supreme Court granted certiorari. This article addresses the issues in the Golan case, literally on the eve of oral argument before the Court. This article first considers the Copyright and Treaty Clauses, and then addresses the relationship between copyright and the First Amendment. The discussion endorses an understanding of that relationship in which the Amendment is newly seen as paramount, and copyright is newly seen in the image of the Amendment

    Post-Racial

    Get PDF
    This image was created by Sam Fleming for Tapestries: Interwoven voices of local and global identities, volume 6 (2017), published by Macalester College.For more information, please visit the Tapestries journal home page. Copyright 2017, Samuel Fleming

    A Framework for Image Segmentation Using Shape Models and Kernel Space Shape Priors

    Get PDF
    ©2008 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or distribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE. This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder.DOI: 10.1109/TPAMI.2007.70774Segmentation involves separating an object from the background in a given image. The use of image information alone often leads to poor segmentation results due to the presence of noise, clutter or occlusion. The introduction of shape priors in the geometric active contour (GAC) framework has proved to be an effective way to ameliorate some of these problems. In this work, we propose a novel segmentation method combining image information with prior shape knowledge, using level-sets. Following the work of Leventon et al., we propose to revisit the use of PCA to introduce prior knowledge about shapes in a more robust manner. We utilize kernel PCA (KPCA) and show that this method outperforms linear PCA by allowing only those shapes that are close enough to the training data. In our segmentation framework, shape knowledge and image information are encoded into two energy functionals entirely described in terms of shapes. This consistent description permits to fully take advantage of the Kernel PCA methodology and leads to promising segmentation results. In particular, our shape-driven segmentation technique allows for the simultaneous encoding of multiple types of shapes, and offers a convincing level of robustness with respect to noise, occlusions, or smearing

    Hands Up Don\u27t Shoot

    Get PDF
    This image was created by Sam Fleming for Tapestries: Interwoven voices of local and global identities, volume 6 (2017), published by Macalester College.For more information, please visit the Tapestries journal home page. Copyright 2017, Samuel Fleming

    Unite or Die

    Get PDF
    This image was created by Sam Fleming for Tapestries: Interwoven voices of local and global identities, volume 6 (2017), published by Macalester College.For more information, please visit the Tapestries journal home page. Copyright 2017, Samuel Fleming

    Knowledge-based segmentation of SAR data with learned priors

    Get PDF
    ©2000 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or distribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE. This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder.DOI: 10.1109/83.821747An approach for the segmentation of still and video synthetic aperture radar (SAR) images is described in this note. A priori knowledge about the objects present in the image, e.g., target, shadow, and background terrain, is introduced via Bayes' rule. Posterior probabilities obtained in this way are then anisotropically smoothed, and the image segmentation is obtained via MAP classifications of the smoothed data. When segmenting sequences of images, the smoothed posterior probabilities of past frames are used to learn the prior distributions in the succeeding frame. We show with examples from public data sets that this method provides an efficient and fast technique for addressing the segmentation of SAR data
    • …
    corecore