Summary of Classification Of Inkjet Printers Based on Droplet Statistics, by Patrick Takenaka et al.
Classification of Inkjet Printers based on Droplet Statistics
by Patrick Takenaka, Manuel Eberhardinger, Daniel Grießhaber, Johannes Maucher
First submitted to arxiv on: 26 Jun 2024
Categories
- Main: Computer Vision and Pattern Recognition (cs.CV)
- Secondary: Artificial Intelligence (cs.AI); Machine Learning (cs.LG); Image and Video Processing (eess.IV)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary In this paper, researchers investigate how to identify the printer model used to print a document. They do this by analyzing the patterns created by inkjet printers and using machine learning techniques to classify the printer model based on these patterns. The authors collect a large dataset of high-resolution scans of documents printed on different printers and show that their method can accurately identify not only the manufacturer but also specific printer models. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This research could help prevent document counterfeiting by allowing authorities to quickly identify the printer used to print a suspicious document. The paper uses machine learning techniques, including neural networks, to analyze the patterns created by inkjet printers and classify them based on their characteristics. By doing this, it may be possible to identify not only the manufacturer of the printer but also specific models. |
Keywords
» Artificial intelligence » Machine learning
