Skip to main content

Thermal Infrared Face Segmentation: A New Pose Invariant Method

  • Conference paper
Pattern Recognition and Image Analysis (IbPRIA 2013)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 7887))

Included in the following conference series:

Abstract

This paper presents a method for automatic segmentation of images of faces captured in (LWIR), allowing a wide range of face rotations, expressions and artifacts (such as glasses and hats). The paper presents a novel high accurate approach and compares its performance against three other previously published methods. The proposed approach is based on statistical modeling of pixel intensities and active contour application, although several other image processing operations are also performed. Experiments were performed on a total of 699 test images from three public available databases. The obtained results improve on previous existing methods up to 29.5% for the first measure error (E 1) and up to 34.7% for the second measure (E 2), depending on the method and database.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 84.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
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

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Similar content being viewed by others

References

  1. Kong, S., Heo, J., Abidi, B., Paik, J., Abidi, M.: Recent advances in visual and infrared face recognition - a review. Computer Vision and Image Understanding 97(1), 103–135 (2005)

    Article  Google Scholar 

  2. Gyaourova, A., Bebis, G., Pavlidis, I.: Fusion of infrared and visible images for face recognition. In: Pajdla, T., Matas, J. (eds.) ECCV 2004, Part IV. LNCS, vol. 3024, pp. 456–468. Springer, Heidelberg (2004)

    Google Scholar 

  3. Pavlidis, I., Tsiamyrtzis, P., Manohar, C., Buddharaju, P.: Biometrics: Face recognition in thermal infrared. In: Biomedical Engineering Handbook, 3rd edn., pp. 1–15. CRC Press (2006)

    Google Scholar 

  4. Cho, S., Wang, L., Ong, W.: Thermal imprint feature analysis for face recognition. In: IEEE International Symposium on Industrial Electronics, pp. 1875–1880 (2009)

    Google Scholar 

  5. Filipe, S., Alexandre, L.A.: Improving Face Segmentation in Thermograms Using Image Signatures. In: Bloch, I., Cesar Jr., R.M. (eds.) CIARP 2010. LNCS, vol. 6419, pp. 402–409. Springer, Heidelberg (2010)

    Chapter  Google Scholar 

  6. Canny, J.: A computational approach to edge detection. IEEE Transactions on Pattern Analysis and Machine Intelligence 8(6), 628–633 (1986)

    Google Scholar 

  7. Chan, T.F., Vese, L.A.: Active contours without edges. IEEE Transactions on Image Processing 10(2), 266–277 (2001)

    Article  MATH  Google Scholar 

  8. Chen, X., Flynn, P., Bowyer, K.: IR and visible light face recognition. Computer Vision and Image Understanding 99, 332–358 (2005)

    Article  Google Scholar 

  9. Miezianko, R.: Terravic Research Infrared Database (2006), http://www.cse.ohio-state.edu/otcbvs-bench/

  10. Abidi, B.: IRIS Thermal/Visible Face Database. DOE University Research Program in Robotics under grant DOE-DE-FG02-86NE37968 (2007)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2013 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Filipe, S., Alexandre, L.A. (2013). Thermal Infrared Face Segmentation: A New Pose Invariant Method. In: Sanches, J.M., Micó, L., Cardoso, J.S. (eds) Pattern Recognition and Image Analysis. IbPRIA 2013. Lecture Notes in Computer Science, vol 7887. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-38628-2_75

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-38628-2_75

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-38627-5

  • Online ISBN: 978-3-642-38628-2

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics