Exploration and Research of Laser Printing Document Traceability Methods in the Context of Big Data

Author:

Tang Yifan

Publisher

Atlantis Press International BV

Reference6 articles.

1. Hao J, Kong X, Shang S. Printer identification using page geometric distortion on text lines[C]//2015 IEEE China Summit and International Conference on Signal and Information Processing (ChinaSIP). IEEE, 2015: 856–860.

2. Jain H, Joshi S, Gupta G, et al. Passive classification of source printer using text-line-level geometric distortion signatures from scanned images of printed documents[J]. Multimedia Tools and Applications, 2020, 79(11-12): 7377–7400.

3. Mikkilineni A K, Chiang P J, Ali G N, et al. Printer identification based on graylevel co-occurrence features for security and forensic applications[C]//Security, steganography, and watermarking of multimedia contents vii. SPIE, 2005, 5681: 430–440.

4. Oliver J, Chen J. Use of signature analysis to discriminate digital printing technologies[C]//NIP & Digital Fabrication Conference. Society for Imaging Science and Technology, 2002, 2002(1): 218–222.

5. Li B, Qu Y, Wang C, et al. Studies about quantitative examination of laser printed documents based on image physical metric[J]. Forensic Science International, 2021, 318: 110–119.

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