A toolkit for detecting and removing the small systematic "yellow" tracking dots that many commercial color laser printers print to encode device-identifying information. It implements extraction, pattern analysis and decoding of these forensic marks and also provides tools to anonymise documents or to generate synthetic dot patterns. The project cites a 2018 forensic analysis by Timo Richter, Stephan Escher, Dagmar Schönfeld and Thorsten Strufe as its research basis and bundles both a graphical interface (deda_gui) and command-line utilities so researchers and practitioners can read out tracking data or prevent tracking.
Installation is via pip (or from source) with an optional Wand dependency for masking white/light graphics; the read workflow expects lossless images (PNG) scanned at 300 dpi with neutral contrast. Key commands include deda_parse_print (decode), deda_compare_prints (find divergent printers), deda_extract_yd (extract dots), deda_create_dots (make custom matrices), deda_clean_document (remove tracking from scans) and deda_anonmask_create / deda_anonmask_apply (create and apply per-printer anonymisation masks: print a calibration page, scan it, generate mask.json, then apply to a PDF). Troubleshooting notes cover PATH and build issues, scanner preprocessing that removes dots, monochrome/inkjet prints that lack dots, options to create or copy masks if dots are absent, and ImageMagick/Wand policy fixes for PDF handling.
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