Paper
18 March 2008 Individuality evaluation for paper based artifact-metrics using transmitted light image
Manabu Yamakoshi, Junichi Tanaka, Makoto Furuie, Masashi Hirabayashi, Tsutomu Matsumoto
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Abstract
Artifact-metrics is an automated method of authenticating artifacts based on a measurable intrinsic characteristic. Intrinsic characters, such as microscopic random-patterns made during the manufacturing process, are very difficult to copy. A transmitted light image of the distribution can be used for artifact-metrics, since the fiber distribution of paper is random. Little is known about the individuality of the transmitted light image although it is an important requirement for intrinsic characteristic artifact-metrics. Measuring individuality requires that the intrinsic characteristic of each artifact significantly differs, so having sufficient individuality can make an artifact-metric system highly resistant to brute force attack. Here we investigate the influence of paper category, matching size of sample, and image-resolution on the individuality of a transmitted light image of paper through a matching test using those images. More concretely, we evaluate FMR/FNMR curves by calculating similarity scores with matches using correlation coefficients between pairs of scanner input images, and the individuality of paper by way of estimated EER with probabilistic measure through a matching method based on line segments, which can localize the influence of rotation gaps of a sample in the case of large matching size. As a result, we found that the transmitted light image of paper has a sufficient individuality.
© (2008) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Manabu Yamakoshi, Junichi Tanaka, Makoto Furuie, Masashi Hirabayashi, and Tsutomu Matsumoto "Individuality evaluation for paper based artifact-metrics using transmitted light image", Proc. SPIE 6819, Security, Forensics, Steganography, and Watermarking of Multimedia Contents X, 68190H (18 March 2008); https://doi.org/10.1117/12.765035
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Cited by 10 scholarly publications.
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KEYWORDS
Image transmission

Image segmentation

Image resolution

Statistical analysis

Biometrics

Error analysis

Resistance

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