Dear friends welcome to this week’s tip! Today we’ll talk about something that is more of a philosophy than a feature, and as such, you’ll find it reflected in all Amped products. We’re talking about the way Amped solutions deal with export formats and project files. We’ll show you how compatible our export formats are and how readable (and… editable!) our project files are, so… keep reading!Continue reading
Dear Amped friends, welcome to one more tip! Following the recent mini-series about unveiling traces of double JPEG compression, today we’ll show how Amped Authenticate can reveal if a seemingly uncompressed image was actually JPEG compressed in its past. Keep reading to find out more!Continue reading
Dear Amped friends, today we’re sharing with you something big. If you’ve been following us, then you know that Amped invests lots of resources into research and testing. We also join forces with several universities to be on the cutting edge of image and video forensics. During one of these research ventures with the University of Florence (Italy), we discovered something important regarding PRNU-based source camera identification.
PRNU-based source camera identification has been, for years, considered one of the most reliable image forensics technologies: given a suitable number of images from a camera, you can use them to estimate the sensor’s characteristic noise (we call it Camera Reference Pattern, CRP). Then, you can compare the CRP against a questioned image to understand whether it was captured by that specific exemplar. You can read more about PRNU here.
Since its beginnings, the real strength of PRNU-based source camera identification was that false positives were extremely rare, as shown in widely acknowledged scientific papers. The uniqueness of the sensor fingerprint was so strong that researchers were even able to cluster images based on their source device, comparing the residual noise extracted from single images, in a one-vs-one fashion. We tested this one-vs-one approach over the VISION dataset, which is composed of images captured with 35 portable devices (released roughly between 2010 and 2015), and actually, it worked. Take a look at the boxplot below. On the X-axis you have the 35 different devices in the VISION dataset (click here to see the list). For each device, the vertical green box shows the PCE values obtained comparing couples of images captured by the device itself (the thick box covers values from the 25th to the 75th percentiles, the circled black dot is the median value, isolated circles are “outlier” values). Red boxes and circles represent the PCE values obtained comparing images of the device against images of other devices. As expected, for most devices the green boxes lay well above the dashed horizontal line sitting on 60, which is the PCE threshold commonly used to claim a positive match. Most noticeably, we have no red circles staying well above the PCE threshold: yes, there are some here and there sporadically, but they’re still at values below 100, so we can call these “weak false positives”.
But with all the computations that happen inside modern devices, is PRNU still equally reliable? To answer this question, we’ve been downloading thousands of images from the web, filtering them so to take only pictures captured with recent (2019+) smartphones. We also filtered out images having traces of editing software in their metadata, and we applied several heuristic rules to exclude images that seemed to be not camera originals. For some devices, we also collected images at two of the default resolutions. We then grouped images by uploading users, assuming that different users take pictures with different exemplars and that a single user only owns one exemplar. Now, take a look at what happened when we tested Samsung smartphones.Continue reading
Dear friends welcome to this week’s tip! Today we’re showing a simple yet very handy feature of Amped FIVE: the Histogram tool. We’ll briefly explain what the image histogram is and how the Histogram tool can help you work your way to a successful image enhancement! So… keep reading!Continue reading
Dear fellows welcome to this week’s tip! When users try Amped Replay, they are always super happy with its graphical interface usability and friendliness. There is usually just one point where they ask for clarification: the various video export options that the software provides. This week’s tip is devoted to clarifying how they differ and when you should use them, so keep reading!Continue reading
Hello dear friends, ready for this week’s tip? Today we’ll be continuing the mini-series about investigating the life-cycle of digital images, specifically revealing previous JPEG compressions with Amped Authenticate. If you missed the first tip, it’s here for you, but you can also just read this one now.Continue reading
Dear loyal summer readers welcome to this week’s tip! As investigators, one of the questions we should always ask ourselves is: “am I using the best possible evidence?”. This is vital to ensure that we can interpret the native data correctly and have the best chance to obtain visual information after any restoration and/or enhancement process. Today we’ll see how Amped FIVE can greatly help you compare two videos at the visual level to understand whether they’re exactly the same or quantify the difference between them. Keep reading!Continue reading
Hello, dear Amped blog fellows! This week we’re beginning a mini-series of two tips dealing with one of my favorite topics, image life-cycle investigation! They’re a bit more technical than usual, but I’m sure you’ll enjoy them. Today, we’ll see how we can use Amped Authenticate to look for traces of previous JPEG compressions in your evidence image, and in the next tip of the series, we’ll deal with estimating the quality of possible previous JPEG compressions. Keep reading!Continue reading
Dear loyal summer readers, thanks for being here instead of having a swim! Today’s tip won’t be long, I promise, but it covers a feature of Amped Replay that I’m sure is unknown to most. Did you know Amped Replay can be configured to enable/disable some of the software functionalities and optionally show messages on the GUI? This can be extremely useful when deploying Replay to different units having different skill levels. Keep reading to know more about it!Continue reading
Dear friends welcome to this week’s tip! I hope you didn’t miss the latest news about Amped Authenticate! With the last Update 17658, we’ve introduced a brand new filter category, called Geometrical Analysis, which includes the Shadows filter. Today we’ll demonstrate how to choose which shadow constraints to be added and which would not add any value. Avoiding useless constraints will make processing faster and produce more pleasant output images. Keep reading!Continue reading