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Database and Data Management Requirements for Equalization of Contactless Acquired Traces for Forensic Purposes—Provenance and Performance

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Abstract

The importance of fingerprints and microtraces within the field of criminalistics and forensics is well-known. An upcoming field is the contactless acquisition of traces, because the integrity of traces is preserved Hildebrandt et al. (MM’Sec, pp. 1–8, 2011). A further issue from such an acquisition method is the potential presence of perspective distortions, which we already started to deal with in Kist et al. (SPIE 8546 Conf., pp. 0A/1–0A/12, 2012). Within the scope of a productive use of contactless acquisition methods, preprocessing steps like the equalization come along. In this paper, we give a perspective on requirements for an underlying database and database management system to support the methods of Kist et al. (SPIE 8546 Conf., pp. 0A/1–0A/12, 2012) as a potential real-case scenario. Thereby, we point out possible starting points for parallelization potential and evaluate the benefit. Finally, we integrate an approach to ensure the chain of custody by means of provenance, which is essential for any forensic investigation and evaluate the effect on the overall system performance.

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Notes

  1. For all scans the confocal laser microscope “Keyence VK-X110” [11] was used; intensity and topography data were used for equalization.

  2. A partial human hair, see Fig. 2 and Table 1.

  3. Equalization of a fingerprint (20 degrees, area: 14.26 mm×9.49 mm): 10.30 minutes—using: Intel(R) Core(TM) i7-2670QM @ 3.1 GHz, 8 GB RAM; JavaVM @ 4 GB, WDC WD6400BPVT-60HXZ.

  4. The surface a trace is present on.

  5. E.g. curved, spherical or inhomogeneously shaped surfaces.

  6. E.g. ridgeline distance, relative position of minutiae.

  7. “NIST Biometric Image Software”—see [online]: http://www.nist.gov/itl/iad/ig/nbis.cfm; minutiae-based.

  8. A planar surface in different angles, two curved surfaces, a spherical surface—see [13].

  9. Significances are shown in curly brackets over each bar in the diagram.

  10. No standard deviation or significance could be calculated.

  11. Using the “Keyence VK-X110”, a scan of a fingerprint of the test set of Table 1 easily exceeds 20 hours.

  12. Two dimensional perspective distortions can not be projected into a distortion-free representation, since none of the surface’s principal curvatures is zero.

  13. On a system, using: Intel(R) Core(TM) i7-2670QM @ 3.1 GHz, 8 GB RAM; JavaVM @ 4 GB, WDC WD6400BPVT-60HXZ.

  14. Data size is given in total: sum of size of intensity- and topography data.

  15. Scan of a partial human hair at 70 degrees (area: 1.35 mm × 1.83 mm).

  16. Complete scan of a fingerprint at 20 degrees (area: 14.26 mm × 9.40 mm).

  17. Value refers to the equalization of a complete scan of a fingerprint at 20 degrees (area: 14.26 mm × 9.40 mm).

  18. The average CPU-time was calculated for 8 consecutive equalizations (based on scans of given test set, see Table 1).

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Acknowledgements

The work in this paper has been funded in part by the German Federal Ministry of Education and Science (BMBF) through the Research Program under Contract No. FKZ:13N10816 and FKZ:13N10817. In addition to that, parts of the data was acquired under FKZ:13N10818.

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Authors and Affiliations

  1. FH Brandenburg, Fachbereich Informatik und Medien, P.O. Box 2132, 14737, Brandenburg an der Havel, Germany

    Stefan Kirst

  2. University of Magdeburg, P.O. Box 4120, 39016, Magdeburg, Germany

    Martin Schäler

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  1. Stefan Kirst
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  2. Martin Schäler
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Correspondence to Stefan Kirst.

Additional information

This is an extended version of the paper “Database and Data Management Requirements for Equalization of Contactless Acquired Traces for Forensic Purposes” [14], selected for the special DASP issue Best Workshop Papers of BTW 2013.

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Kirst, S., Schäler, M. Database and Data Management Requirements for Equalization of Contactless Acquired Traces for Forensic Purposes—Provenance and Performance. Datenbank Spektrum 13, 201–211 (2013). https://doi.org/10.1007/s13222-013-0141-y

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