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How to Investigate Which Camera Model Took an Image Using Exif Metadata and JPEG Quantization Tables

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Welcome, dear Amped blog maniacs! Digital image forensics people have a bittersweet relationship with metadata. We love them… but can we trust them? Today’s tip is about cross-checking Exif metadata information about the camera model that allegedly created your evidence image. We’ll see that Amped Authenticate‘s JPEG Quantization Tables are a great resource, making your integrity verification far more reliable. Keep reading to find out more.

Understanding the Limitations of Exif Metadata in Forensics

If you know a bit about JPEG compression, or you have attended our Amped Authenticate training, then you know that JPEG Quantization Tables are a great resource for digital image integrity analysis. When you’re doing integrity analysis, one of the first questions you ask yourself is: “which device model was used to capture this image?”. Normally, it doesn’t take much to reach the first answer. Most devices today write their brand and model straight in the image metadata, as you can read in the Exif filter. Not only: when this information is available, Authenticate will also read it and show it in the top bar for your convenience (red arrow below).

Screenshot of Amped Authenticate software displaying EXIF metadata from a JPEG image file located at C:\demo\DSC_0359.JPG. The metadata reveals the camera make as "NIKON CORPORATION" and model as "NIKON D50". The interface shows the EXIF filter selected, highlighting key photographic parameters such as orientation, resolution, and exposure details.

Exif metadata are nice, but they do have a drawback: they can be easily altered. The Make and Model metadata, coincidentally, are probably the easiest to alter. If you’re a Windows user, the simple File Explorer is enough. Right-click on your image file, click on Properties, then go to the Details tab and there they are!

Image of the DSC_0359.JPG Properties window on a Windows system, showing detailed metadata under the "Details" tab. The Camera section lists the camera maker as "NIKON CORPORATION" and model as "NIKON D50". Additional photo metadata includes F-stop (f/5.6), exposure time (1/125 sec), ISO speed, focal length (18 mm), and no flash used. A red arrow highlights the camera information section.

The forensic man in you will shiver with terror realizing that those fields in the property tab are… editable!

Close-up of the Camera metadata section in a photo properties window showing an edited Camera model field changed to “THE HACKER I AM,” while the Camera maker remains “NIKON CORPORATION.” Other details include f-stop (f/5.6), exposure time (1/125 sec), ISO speed, and focal length (18 mm).

How JPEG Quantization Tables Support Exif Metadata Verification

That is to say: metadata shouldn’t be your single point of truth. And so? Don’t worry, we have good news! When saving an image, cameras leave many other “less intentional” signatures. Among these, there’s one that is quite distinctive, easy to understand, and hard to edit: the JPEG Quantization Table (often abbreviated in JPEG QT). Without going into too much detail, a JPEG QT is an 8-by-8 matrix of integer values used during JPEG compression. It’s written in the file header because it’s necessary to reconstruct the file (decompress).

Contrary to what happens with metadata, it’s not trivial at all to change the JPEG QT of an image file without recompressing it from scratch. Even if you decide to recompress your image, choosing a specific quantization table may not be possible. Most software and cameras only let you select a “quality factor” from a predefined list. This quality factor is then automatically mapped to one of the internal JPEG Quantization Tables used by the software or camera.

Typically, each image contains two or more quantization tables: one for luminance and the other for color. Additionally, if the image includes a thumbnail, it will also have its own JPEG Quantization Tables. For simplicity, we will focus only on the main image’s luminance quantization table.

The interesting aspect is that, while the JPEG Standard offers a recommended set of quantization tables, most camera manufacturers have developed their own unique tables. Moreover, these often use different quantization tables for various camera models within their brand. This is the reason why JPEG QTs are considered a real asset in source camera model verification. You can check whether the JPEG QTs of your evidence image are compatible with those used by the camera model declared in Exif metadata. Of course, to do so you need a database where JPEG QTs are linked to the compatible camera models.

We love to give you good news. When you get Amped Authenticate, you’re also getting a huge database of 14.000+ quantization tables associated with the compatible camera brand and model. Just click on the JPEG QT filter, and Authenticate will automatically list all the cameras in the database that are compatible with your image’s QT.

In the example below, we see that the image quantization table is compatible with a lot of Canon cameras, among which there’s the one declared in the Exif metadata!

Screenshot of Amped Authenticate software showing JPEG QT analysis for an image labeled “canon_eos_40d.jpg.” The EXIF metadata confirms the camera brand and model as Canon EOS 40D, with a matching JPEG Quantization Table (QT). The interface highlights the JPEG QT of the evidence image, a list of compatible cameras sharing the same QT, and confirms a metadata match.

Since this cross-check is very important, Authenticate does it for you automatically. When you click on the File Format filter, there’s a line dedicated to warn you when:

  • The camera model declared in Exif metadata is not present in Authenticate’s database;

Screenshot of Amped Authenticate displaying metadata analysis for an image taken with a Google Pixel 3a. The JPEG image has a resolution of 4032x3024, quality 95%, and includes detailed EXIF data. A warning message highlights that no compression signature is available in the database for this specific camera model.

  • The camera model declared in your image’s Exif metadata is present in the database. But, is not associated with your image’s JPEG QT.

Screenshot of Amped Authenticate showing metadata analysis for a JPEG image taken with a Nikon D50 camera. The analysis reveals a message stating “Compression signature not found in the DB for this camera,” indicating that the database lacks a matching compression signature for verification. The image resolution is 3008x2000 with a JPEG quality of 53%.

Best Practices for Cross-Checking Camera Models with Exif Metadata

In both cases, we recommend that you obtain reference images to compare with. For example, with Authenticate you can quickly search the web for other images from the same camera model.

If you need to check whether a specific camera model is present in the Amped Authenticate JPEG QT database, just head to the JPEG QT filter and click on the View All QTs in Database button. A window pops up, where you want to choose Internal camera from the Group dropdown menu. Entries are sorted by Make and then by Model.

Screenshot of Amped Authenticate software showing JPEG Quantization Table (QT) database view. The left sidebar highlights the "JPEG QT" analysis tab (Step 1), the main interface shows a list of Samsung camera models and their associated QT hashes (Step 2), and the group filter is set to “Internal Camera” (Step 3). This interface supports forensic image source validation by comparing JPEG compression signatures against a camera database.

Final Note

We note once more that Exif metadata is just text written in your image file header. JPEG Quantization Tables are stored differently and can hardly be altered. Thus, if you can cross-check brand and model info obtained through Exif metadata and JPEG Quantization Tables, that’s a great added value to your integrity verification.


 Marco Fontani

Marco Fontani is the Forensics Director at Amped Software, a software company developing image and video forensic solutions for law enforcement agencies worldwide. He earned his MSc in Computer Engineering in 2010 and his Ph.D. in Information Engineering in 2014. His research focused on image watermarking and multimedia forensics. He participated in several research projects funded by the EU and EOARD, and authored/co-authored over 30 journal and conference proceedings papers. He has experience in delivering training to law enforcement and provided expert witness testimony on several forensic cases involving digital images and videos. He is a former member of the IEEE Information Forensics and Security Technical Committee, and he actively contributed to the development of ENFSI’s Best Practice Manual for Image Authentication.

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