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DEDA is a software toolkit for extracting and sometimes decoding tracking dots embedded in color laser prints, and for masking those patterns to reduce tracking. Its GitHub documentation describes analysis and anonymisation workflows, but does not establish how widely the tool is used or guarantee that masking removes every identifying feature.
The DEDA toolkit provides software to extract and sometimes decode tracking dots from scanned prints, and to mask those patterns in documents prepared for printing. The project’s GitHub documentation says the dots—also called document colour tracking dots or “yellow dots”—can encode information about a printer or printout, potentially including a device serial number, giving users ways to inspect and reduce one source of printer-based identification.
DEDA’s repository describes the dots as small, systematic marks used in almost every commercial colour laser printer. It says the toolkit can read tracking data from scans, compare prints, extract unfamiliar dot patterns for further analysis, and create dot matrices. The documentation does not claim that every printer or every printed page carries such marks: it specifically cautions that monochrome pages and inkjet prints might not contain them.
The project lists separate workflows for scans and print-ready files. Users can run a parser on a scanned image, with the documentation recommending lossless input such as PNG at 300 dpi and neutral contrast. Another function creates a printer-specific mask from a calibration page; that mask can then be applied to a PDF before printing. A separate command is described as mostly removing tracking data from a scan.
These are instructions and capabilities documented by the project, not independent test results showing how reliably the toolkit works across printers. The repository asks users who use the software to cite a 2018 ACM workshop paper by Timo Richter, Stephan Escher, Dagmar Schönfeld and Thorsten Strufe, titled “Forensic Analysis and Anonymisation of Printed Documents.”
Reducing Printer-Based Identification
Printer tracking dots matter because they can link a physical print to information about the device that produced it. If encoded data identifies a printer or printout, a document distributed without its author’s name may still carry a technical clue about its source. DEDA makes that feature inspectable and offers a way to mask it, giving researchers and privacy-conscious users a practical means to examine one potential source of identifying information.
The limits matter as much as the stated purpose. DEDA’s documentation describes masking as a technical process, not a guarantee of anonymity. It advises checking a masked page under a microscope to see whether the mask covers the printer’s dots. The toolkit also addresses only tracking patterns; its description does not say that it removes other identifying details, such as visible text, metadata or distinctive content.
printer tracking dots analysis software
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How DEDA Handles Dot Patterns
The repository presents DEDA as a Python package installable through PyPI or from its source directory, with both a graphical interface and command-line programs. The listed tools cover several stages: reading known tracking data, comparing multiple scanned prints, extracting dots from patterns the parser does not recognise, creating a dot matrix, and applying anonymisation measures.
For print anonymisation, the documented process first uses a calibration page printed without margins and scanned at 300 dpi. DEDA uses that scan to create a mask adjusted to the individual printer; users then apply the mask to a PDF and print the resulting file with zero margins. The project notes that masking white or light areas in graphics requires the optional Wand dependency. These details show that the method depends on printer-specific calibration and suitable scanning and printing settings.
The cited research paper appeared in the proceedings of the sixth ACM Workshop on Information Hiding and Multimedia Security in 2018. The repository’s documentation also notes that scans can fail to reveal dots if scanning software removes paper texture or applies thresholding. That warning underlines that a missing detected pattern is not, by itself, proof that a printer does not produce tracking marks.
““This tool gives the possibility to read out and decode these forensic features” and “allows anonymisation to prevent arbitrary tracking.””
— DEDA project documentation
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Masking Limits and Project Status
The supplied project material does not establish the toolkit’s current maintenance status, the range of printer models tested, or an independently measured success rate for detecting or masking dots. It also does not quantify how often dot patterns encode a serial number or other identifying information. The repository’s broad statement about commercial colour laser printers is not accompanied in the supplied material by a current industry survey.
It remains unclear how effective the masking workflow is against different printer settings, paper types, scan processing and page content. The project itself says that light-coloured graphics may need an optional dependency, that scans may lose dots through thresholding, and that users should inspect results microscopically. Its claim that scan cleaning removes tracking data “mostly” is qualified, and the documentation does not promise complete removal or anonymity.
printer tracking dot masking software
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Checks Before Relying on DEDA
The immediate next step for anyone evaluating DEDA is to consult the project repository and cited 2018 paper for the relevant code, installation requirements and methodological details. The documentation recommends testing the process on the specific printer, scanning at the stated resolution with lossless compression, and inspecting masked output rather than treating a successful command as proof that all dots are covered.
No new release, independent evaluation or project update is identified in the supplied material. Until such information is available, the toolkit’s present support status and performance across current printers remain open questions. Users should treat it as a tool for investigating and reducing one possible tracking channel, not as proof that a document is untraceable.
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Key Questions
What does DEDA do?
DEDA is a toolkit for extracting and sometimes decoding printer tracking dots, comparing printed documents, and masking dot patterns in scans or print-ready PDFs.
What are printer tracking dots?
They are small, systematic marks—also called document colour tracking dots or yellow dots—that the project says can encode information about a printer or printout, potentially including a device serial number.
Does every printed page contain tracking dots?
No. DEDA’s documentation says monochrome pages and inkjet prints might not contain them. It also warns that scan processing can remove or obscure the paper structure and dots.
Does DEDA guarantee an anonymous print?
No such guarantee appears in the documentation. The tool is intended to mask tracking patterns, but users are told to inspect the result under a microscope, and the software does not claim to remove every possible identifying feature.
What scan settings does the project recommend?
For reading tracking data, the repository recommends a lossless image, such as PNG, at 300 dpi with neutral contrast.
Source: hn
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