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Published in:
2011 | OriginalPaper | Chapter
Fingerprints for Machines – Characterization and Optical Identification of Grinding Imprints
Authors : Ralf Dragon, Tobias Mörke, Bodo Rosenhahn, Jörn Ostermann
Published in: Pattern Recognition
Publisher: Springer Berlin Heidelberg
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The profile of a 10mm wide and 1
μ
m deep grinding imprint is as unique as a human fingerprint. To utilize this for fingerprinting mechanical components, a robust and strong characterization has to be used. We propose a feature-based approach, in which features of a 1D profile are detected and described in its 2D space-frequency representation. We show that the approach is robust on depth maps as well as intensity images of grinding imprints. To estimate the probability of misclassification, we derive a model and learn its parameters. With this model we demonstrate that our characterization has a false positive rate of approximately 10
− 20
which is as strong as a human fingerprint.