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A Tire Tread Pattern Detection Based on Fuzzy Logic

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Book cover Flexible Query Answering Systems 2015

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 400))

Abstract

Tire tread prints, being common type of evidence at crime scene, contain useful information for the investigator. To determine the brand or manufacturer of a tire related to the tread, database of tire treads is required. It can be built using thousands of tire photographs available in many existing web shops. To build such a database tire photographs must be downloaded and processed automatically.

In this paper we present a method to automatically detect tire tread in provided image from existing database. Our aim is to find ellipses which determine tire tread sample. In the first step we use Hough transform to detect all ellipses from provided image. In the second step the set of ellipses is reduced by fuzzy inference system to select those which describe position of tire tread sample the best and finally at the end we present results of experiments.

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References

  1. Geradts, Z., Keijzer, J.: The image-database REBEZO for shoeprints with developments on automatic classification of shoe outsole designs. Forensic Science International 82(1), 21–31 (1996)

    Article  Google Scholar 

  2. Thali, M.J., Braun, M., Brschweiler, W., Dirnhofer, R.: Matching Tire Tracks on the Head Using Forensic Photogrammetry. Forensic Science International 113(1–3), 281–287 (2000)

    Article  Google Scholar 

  3. Chazal, P., Flynn, J., Reilly, R.B.: Automated processing of shoeprint images based on the Fourier transform for use in forensic science. IEEE Transactions on Pattern Analysis and Machine Intelligence 27(3), 341–350 (2005). IEEE Computer Society Washington, DC, USA

    Article  Google Scholar 

  4. Zhang, L., Allinson, N.: Automatic shoeprint retrieval system for use in forensic investigations. In: 5th Annual UK Workshop on Computational Intelligence (2005)

    Google Scholar 

  5. Pavlou, M., Allinson, N.: Automated Encoding of Footwear Patterns for Fast Indexing. Image and Vision Computing 27(4), 402–409 (2009). Butterworth-Heinemann, Newton, MA, USA

    Article  Google Scholar 

  6. Nibouche, O., Bouridane, A., Crookes, D., Gueham, M., Laadjel, M.: Rotation invariant matching of partial shoeprints. In: Proceedings of the 13th Machine Vision and Image Processing Conference, pp. 94–98. IEEE Computer Society, Washington, DC, USA (2009)

    Google Scholar 

  7. Jing, M.Q., Ho, W.J., Chen, L.H.: A novel method for shoeprints recognition and classification. In: International Conference on Machine Learning and Cybernetics, vol. 5, pp. 2846–2851. IEEE (2009)

    Google Scholar 

  8. Dardi, F., Cervelli, F., Carrato, S.: A texture based shoe retrieval system for shoe marks of real crime scenes. In: Foggia, P., Sansone, C., Vento, M. (eds.) ICIAP 2009. LNCS, vol. 5716, pp. 384–393. Springer, Heidelberg (2009)

    Chapter  Google Scholar 

  9. Wang, R., Hong, W., Yang, N.: The research on footprint recognition method based on wavelet and fuzzy neural network. In: Ninth International Conference on Hybrid Intelligent Systems, vol. 3, pp. 428–432. IEEE (2009)

    Google Scholar 

  10. Patil, P.M., Kulkarni, J.V.: Rotation and Intensity Invariant Shoeprint Matching Using Gabor Transform with Application to Forensic Science. Pattern Recognition 42(7), 1308–1317 (2009). Elsevier Science Inc., New York, NY, USA

    Article  Google Scholar 

  11. Huang, D.-Y., Hu, W.-C., Wang, Y.-W., Chen, C.-I., Cheng, C.-H.: Recognition of tire tread patterns based on gabor wavelets and support vector machine. In: Pan, J.-S., Chen, S.-M., Nguyen, N.T. (eds.) ICCCI 2010, Part III. LNCS, vol. 6423, pp. 92–101. Springer, Heidelberg (2010)

    Google Scholar 

  12. Tang, Y., Kasiviswanathan, H., Srihari, S.N.: An efficient clustering-based retrieval framework for real crime scene footwear marks. In: Int. J. Granular Computing Rough Sets and Intelligent Systems, vol. 2, no. 4, pp. 327–360 (2012)

    Google Scholar 

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Author information

Authors and Affiliations

  1. Department of Computer Science, Faculty of Science, Matej Bel University, Tajovského 40, 97401, Banská Bystrica, Slovakia

    Alžbeta Michalíková & Michal Vagač

Authors
  1. Alžbeta Michalíková
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  2. Michal Vagač
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Corresponding author

Correspondence to Michal Vagač .

Editor information

Editors and Affiliations

  1. Dept. of Comm., Business & Info. Tech., Roskilde University, Roskilde, Denmark

    Troels Andreasen

  2. Dept. Computer Science, Roskilde University, Roskilde, Denmark

    Henning Christiansen

  3. Sys Res Intit of Polish Acad of Science, Intelligent Systems Laboratory, Warsaw, Poland

    Janusz Kacprzyk

  4. Department of Electronic Systems, Aalborg University, Esbjerg, Denmark

    Henrik Larsen

  5. Computer Science Department, University Milano-Biccoca, Milano, Italy

    Gabriella Pasi

  6. IRISA, University of Rennes I, Rennes, France

    Olivier Pivert

  7. Dept. of Tele. & Info. Processing, Ghent University, Gent, Belgium

    Guy De Tré

  8. Dept. of Comp. & Art. Int. Sci., University of Granada, Granada, Spain

    Maria Amparo Vila

  9. Department of Computer Engineering, Middle East Technical University, Ankara, Turkey

    Adnan Yazici

  10. Systems Research Institute, Polish Academy of Sciences, Warsaw, Poland

    Sławomir Zadrożny

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© 2016 Springer International Publishing Switzerland

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Michalíková, A., Vagač, M. (2016). A Tire Tread Pattern Detection Based on Fuzzy Logic. In: Andreasen, T., et al. Flexible Query Answering Systems 2015. Advances in Intelligent Systems and Computing, vol 400. Springer, Cham. https://doi.org/10.1007/978-3-319-26154-6_29

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  • DOI: https://doi.org/10.1007/978-3-319-26154-6_29

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-26153-9

  • Online ISBN: 978-3-319-26154-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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