Skip to main content

LS Footwear Database - Evaluating Automated Footwear Pattern Analysis

  • Conference paper
  • 3654 Accesses

Part of the Lecture Notes in Computer Science book series (LNTCS,volume 5769)


Footwear marks recovered from crime scenes are an important source of forensic intelligence or evidence - for some crime types, there is a greater probably to recover footwear marks than fingerprint ones. Currently the process of identifying a specific shoe model from the 10,000s of possibilities is a time-consuming task for expert examiners. As with many other crime marks, for example latent fingerprints, there is an increasing need for automation. The emergent research effort in this field has been hampered by the lack of a suitable dataset of footwear impressions. We present, here, a substantial and fully characterized dataset together with a proposed methodology for its use.


  • Face Recognition
  • Crime Scene
  • Pattern Class
  • Forensic Setting
  • Latent Fingerprint

These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

This is a preview of subscription content, access via your institution.

Buying options

USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
USD   129.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   169.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. Bodziak, W.J. (ed.): Footwear Impression Evidence. CRC Press, Boca Raton (2000)

    Google Scholar 

  2. Hilderbrand, D.S. (ed.): Footwear, The Missed Evidence. Staggs Publishing (1999)

    Google Scholar 

  3. Pavlou, M., Allinson, N.M.: Footwear Recognition. In: Encyclopedia of Biometrics, pp. 1–10. Springer, Heidelberg (2009)

    Google Scholar 

  4. Pavlou, M., Allinson, N.M.: Automated encoding of footwear patterns for fast indexing. Image and Vision Computing 27(4), 402–409 (2009)

    CrossRef  Google Scholar 

  5. Alexander, A., Bouridane, A., Crookes, D.: Automatic classi cation and recognition of shoeprints. In: Proc. Seventh International Conference on (Conf Image Processing and Its Applications Publ. No. 465), July 13–15, vol. 2, pp. 638–641 (1999)

    Google Scholar 

  6. Bouridane, A., Alexander, A., Nibouche, M., Crookes, D.: Application of fractals to the detection and classi cation of shoeprints. In: Proc. International Conference on Image Processing, September 10–13, vol. 1, pp. 474–477 (2000)

    Google Scholar 

  7. de Chazal, P., de Chazal, P., Flynn, J., Reilly, R.: Automated processing of shoeprint images based on the fourier transform for use in forensic science. Transactions on Pattern Analysis and Machine Intelligence 27(3), 341–350 (2005)

    CrossRef  Google Scholar 

  8. Su, H., Crookes, D., Bouridane, A., Gueham, M.: Local image features for shoeprint image retrieval. In: British Machine Vision Conference 2007 (2007)

    Google Scholar 

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

    Google Scholar 

  10. Everingham, M., Van Gool, L., Williams, C.K.I., Winn, J., Zisserman, A.: The PASCAL Visual Object Classes Challenge 2007 (VOC 2007) Results (2007),

  11. Jain, A., Duin, R., Jianchang, M.: Statistical pattern recognition: a review. IEEE Transactions on Pattern Analysis and Machine Intelligence 22(1), 4–37 (2000)

    CrossRef  Google Scholar 

  12. Phillips, P., Flynn, P., Scruggs, T., Bowyer, K., Chang, J., Hoffman, K., Marques, J., Min, J., Worek, W.: Overview of the face recognition grand challenge. In: IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2005, June 2005, vol. 1, pp. 947–954 (2005)

    Google Scholar 

  13. Li, S.Z., Jain, A.K. (eds.): Handbook of Face Recognition. Springer, Heidelberg (2005)

    MATH  Google Scholar 

  14. Datta, R., Joshi, D., Li, J., Wang, J.Z.: Image retrieval: Ideas, influences, and trends of the new age. ACM Compututing Surveys 40(2), 1–60 (2008)

    CrossRef  Google Scholar 

  15. Kulkarni, S., Lugosi, G., Venkatesh, S.: Learning pattern classi cation-a survey. IEEE Transactions on Information Theory 44(6), 2178–2206 (1998)

    CrossRef  MathSciNet  MATH  Google Scholar 

  16. Poggio, T., Rifkin, R., Mukherjee, S., Niyogi, P.: General conditions for predictivity in learning theory. Nature 428(6981), 419–422 (2004)

    CrossRef  Google Scholar 

  17. Fawcett, T.: An introduction to roc analysis. Pattern Recognition Letters 27(8), 861–874 (2006); ROC Analysis in Pattern Recognition

    CrossRef  MathSciNet  Google Scholar 

  18. Makhoul, J., Kubala, F., Schwartz, R., Weischedel, R.: Performance measures for information extraction. In: Proceedings of DARPA Broadcast News Workshop, pp. 249–252 (1999)

    Google Scholar 

Download references

Author information

Authors and Affiliations


Editor information

Editors and Affiliations

Rights and permissions

Reprints and Permissions

Copyright information

© 2009 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Pavlou, M., Allinson, N.M. (2009). LS Footwear Database - Evaluating Automated Footwear Pattern Analysis. In: Alippi, C., Polycarpou, M., Panayiotou, C., Ellinas, G. (eds) Artificial Neural Networks – ICANN 2009. ICANN 2009. Lecture Notes in Computer Science, vol 5769. Springer, Berlin, Heidelberg.

Download citation

  • DOI:

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-04276-8

  • Online ISBN: 978-3-642-04277-5

  • eBook Packages: Computer ScienceComputer Science (R0)