Bloodstain Pattern Analysis - A New Challenge for Computational Intelligence Community

Giovanni Acampora, Autilia Vitiello, Ciro Di Nunzio, Maurizio Saliva, Luciano Garofano

Abstract

Bloodstain pattern analysis (BPA) is a forensic discipline that plays a key role in tracing events which caused a bloodshed at a crime scene. Indeed, BPA supports worldwide investigation agencies (US FBI, Italian Carabinieri and so on) in interpreting the morphology and distribution of bloodspots at a crime scene in order to enable a potentially complete reconstruction of the dynamics of the act of violence with a consequent identification of potential suspects for that crime. However, in spite of its importance, this forensic discipline is still based on completely manual approaches, making the analysis of a crime scene long, tedious and potentially imperfect. This position paper is aimed at proving that computational intelligence methodologies can be efficiently integrated with image processing techniques to support forensic investigators in increasing their performance in examining bloodstains, both in terms of time and accuracy of analysis. A preliminary study involving the application of fuzzy clustering has been carried out in order to validate our opinion and stimulate computational intelligence community to face this new challenge towards a formal definition of Forensic Intelligence.

References

  1. Bezdek, J. C. (1981). Pattern Recognition with Fuzzy Objective Function Algorithms. Kluwer Academic Publishers, Norwell, MA, USA.
  2. Boonkhong, K., Karnjanadecha, M., and Aiyarak, P. (2010). Impact angle analysis of bloodstains using a simple image processing technique. Sonklanakarin Journal of Science and Technology, 32(2):169.
  3. Brodbeck, S. (2012). Introduction to bloodstain pattern analysis. Practice (Vol. 2), 51:57.
  4. Fitzgibbon, A., Pilu, M., and Fisher, R. (1999). Direct least square fitting of ellipses. Pattern Analysis and Machine Intelligence, IEEE Transactions on, 21(5):476- 480.
  5. James, S. H., Kish, P. E., and Sutton, T. P. (2005). Principles of bloodstain pattern analysis: theory and practice. CRC Press.
  6. Rousseeuw, P. J. (1987). Silhouettes: A graphical aid to the interpretation and validation of cluster analysis. Journal of Computational and Applied Mathematics, 20(0):53 - 65.
  7. Shen, A. R., Brostow, G. J., and Cipolla, R. (2006). Toward automatic blood spatter analysis in crime scenes. In Crime and Security, 2006. The Institution of Engineering and Technology Conference on, pages 378-383. IET.
Download


Paper Citation


in Harvard Style

Acampora G., Vitiello A., Di Nunzio C., Saliva M. and Garofano L. (2014). Bloodstain Pattern Analysis - A New Challenge for Computational Intelligence Community . In Proceedings of the International Conference on Fuzzy Computation Theory and Applications - Volume 1: FCTA, (IJCCI 2014) ISBN 978-989-758-053-6, pages 211-216. DOI: 10.5220/0005155602110216


in Bibtex Style

@conference{fcta14,
author={Giovanni Acampora and Autilia Vitiello and Ciro Di Nunzio and Maurizio Saliva and Luciano Garofano},
title={Bloodstain Pattern Analysis - A New Challenge for Computational Intelligence Community},
booktitle={Proceedings of the International Conference on Fuzzy Computation Theory and Applications - Volume 1: FCTA, (IJCCI 2014)},
year={2014},
pages={211-216},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005155602110216},
isbn={978-989-758-053-6},
}


in EndNote Style

TY - CONF
JO - Proceedings of the International Conference on Fuzzy Computation Theory and Applications - Volume 1: FCTA, (IJCCI 2014)
TI - Bloodstain Pattern Analysis - A New Challenge for Computational Intelligence Community
SN - 978-989-758-053-6
AU - Acampora G.
AU - Vitiello A.
AU - Di Nunzio C.
AU - Saliva M.
AU - Garofano L.
PY - 2014
SP - 211
EP - 216
DO - 10.5220/0005155602110216