Filipe de O. Costa

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Today, a simple search for an image on the Web can return thousands of related images. Some results are exact copies, some are variants (or near-duplicates) of the same digital image, and others are unrelated. Although we can recognize some of these images as being semantically similar, it is not as straightforward to find which image is the original. It is(More)
Camera attribution approaches in digital image forensics have most often been evaluated in a closed set context, whereby all devices are known during training and testing time. However, in a real investigation, we must assume that innocuous images from unknown devices will be recovered, which we would like to remove from the pool of evidence. In pattern(More)
Similar to ballistic tests in which we match a gun to its bullets, we can identify a given digital camera that acquired an image under investigation. In this paper, we discuss a method for identifying whether or not an image was captured by a specific digital camera. The method relies on noise residual features related to the images under investigation. Our(More)
In the last few years, the amount of videos distributed online has dramatically increased due to the popularity of media sharing platforms (e.g., YouTube, Vimeo, etc.). However, distributed videos are often edited copies of original content, typically referred to as near duplicates. In this paper, we face the problem of reconstructing a video phylogeny(More)
Image phylogeny is the problem of reconstructing the structure that represents the history of generation of semantically similar images (e.g., near-duplicate images). Typical image phylogeny approaches break the problem into two steps: (1) estimating the dissimilarity between each pair of images and (2) reconstructing the phylogeny structure. Given that the(More)
Multimedia phylogeny is a research field that aims at tracing back past history of multimedia documents to discover their ancestral relationships. As an example, it might leverage, with the aid of other side information, forensic analysts to detect who was the first user that published online an illegal content (e.g., child pornography). Although relatively(More)
  • INSTITUTO DE COMPUTAÇÃO, ESTADUAL DE CAMPINAS, +4 authors Anderson Rocha
  • 2012
Similar to ballistic tests in which we match a gun to its bullets, we can identify a given digital camera that acquired an image under investigation. In this paper, we introduce a method for identifying whether or not an image was captured by a specific digital camera. The method relies on well-known and established noise residual features related to the(More)
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