Skip to main content
SpringerLink
Log in

Human Skin Segmentation Improved by Saliency Detection

  • Conference paper
  • First Online:
Computer Analysis of Images and Patterns (CAIP 2015)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 9257))

Included in the following conference series:

Abstract

Several applications demand the segmentation of images in skin and non-skin regions, such as face recognition, hand gesture detection, nudity recognition, among others. Human skin detection is still a challenging task since it depends on inumerous factors, for instance, illumination conditions, ethnicity variation and image resolution. This work proposes and analyzes a skin segmentation method improved by saliency detection. Experimental results on public data sets demonstrate significant improvement of the proposed skin segmentation method over state-of-the-art approaches.

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

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
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.

References

  1. Achanta, R., Estrada, F.J., Wils, P., Süsstrunk, S.: Salient region detection and segmentation. In: Gasteratos, A., Vincze, M., Tsotsos, J.K. (eds.) ICVS 2008. LNCS, vol. 5008, pp. 66–75. Springer, Heidelberg (2008)

    Chapter  Google Scholar 

  2. Cheddad, A., Condell, J., Curran, K., Mc Kevitt, P.: A Skin Tone Detection Algorithm for an Adaptive Approach to Steganography. Signal Processing 89(12), 2465–2478 (2009)

    Article  MATH  Google Scholar 

  3. Cheng, M.M., Zhang, G.X., Mitra, N.J., Huang, X., Hu, S.M.: Global contrast based salient region detection. In: IEEE Conference on Computer Vision and Pattern Recognition, pp. 409–416. IEEE (2011)

    Google Scholar 

  4. Fritsch, J., Lang, S., Kleinehagenbrock, M., Fink, G.A., Sagerer, G.: Improving adaptive skin color segmentation by incorporating results from face detection. In: 11th IEEE International Workshop on Robot and Human Interactive Communication, pp. 337–343 (2002)

    Google Scholar 

  5. Goferman, S., Zelnik-Manor, L., Tal, A.: Context-Aware Saliency Detection. IEEE Transactions on Pattern Analysis and Machine Intelligence 34(10), 1915–1926 (2012)

    Article  Google Scholar 

  6. Guo, C., Ma, Q., Zhang, L.: Spatio-temporal saliency detection using phase spectrum of quaternion fourier transform. In: IEEE Conference on Computer Vision and Pattern Recognition, pp. 1–8. IEEE (2008)

    Google Scholar 

  7. Hou, X., Harel, J., Koch, C.: Image Signature: Highlighting Sparse Salient Regions. IEEE Transactions on Pattern Analysis and Machine Intelligence 34(1), 194–201 (2012)

    Article  Google Scholar 

  8. Hou, X., Zhang, L.: Saliency detection: a spectral residual approach. In: IEEE Conference on Computer Vision and Pattern Recognition, pp. 1–8. IEEE (2007)

    Google Scholar 

  9. Jiang, Z., Yao, M., Jiang, W.: Skin detection using color, texture and space information. In: Fourth International Conference on Fuzzy Systems and Knowledge Discovery, vol. 3, pp. 366–370 (2007)

    Google Scholar 

  10. Jones, M.J., Rehg, J.M.: Statistical Color Models with Application to Skin Detection. International Journal of Computer Vision 46(1), 81–96 (2002)

    Article  MATH  Google Scholar 

  11. Kakumanu, P., Makrogiannis, S., Bourbakis, N.: A Survey of Skin-Color Modeling and Detection Methods. Pattern Recognition 40(3), 1106–1122 (2007)

    Article  MATH  Google Scholar 

  12. Kawulok, M.: Energy-based Blob Analysis for Improving Precision of Skin Segmentation. Multimedia Tools and Applications 49(3), 463–481 (2010)

    Article  Google Scholar 

  13. Kawulok, M.: Fast propagation-based skin regions segmentation in color images. In: 10th IEEE International Conference and Workshops on Automatic Face and Gesture Recognition, pp. 1–7 (2013)

    Google Scholar 

  14. Kawulok, M., Nalepa, J., Kawulok, J.: Skin detection and segmentation in color images. In: Advances in Low-Level Color Image Processing, pp. 329–366. Springer (2014)

    Google Scholar 

  15. Kovac, J., Peer, P., Solina, F.: Human skin color clustering for face detection. In: International Conference on Computer as a Tool (Eurocon), vol. 2, pp. 144–148, September 2003. IEEE

    Google Scholar 

  16. Ng, P., Pun, C.M.: Skin color segmentation by texture feature extraction and K-mean clustering. In: Third International Conference on Computational Intelligence, Communication Systems and Networks, pp. 213–218. IEEE (2011)

    Google Scholar 

  17. Phung, S.L., Bouzerdoum, A., Chai Sr, D.: Skin Segmentation using Color Pixel Classification: Analysis and Comparison. IEEE Transactions on Pattern Analysis and Machine Intelligence 27(1), 148–154 (2005)

    Article  Google Scholar 

  18. Phung, S.L., Chai, D., Bouzerdoum, A.: Adaptive skin segmentation in color images. In: International Conference on Multimedia and Expo, vol. 3, pp. III-173 (2003)

    Google Scholar 

  19. Santos, A., Pedrini, H.: A self-adaptation method for human skin segmentation based on seed growing. In: 10th International Conference on Computer Vision Theory and Applications, pp. 455–462. Berlin, Germany (March 2015)

    Google Scholar 

  20. Saxen, F., Al-Hamadi, A.: Color-based skin segmentation: an evaluation of the state of the art. In: IEEE International Conference on Image Processing, pp. 4467–4471. IEEE (2014)

    Google Scholar 

  21. Sobottka, K., Pitas, I.: A Novel Method for Automatic Face Segmentation, Facial Feature Sxtraction and Tracking. Signal Processing: Image Communication 12(3), 263–281 (1998)

    Google Scholar 

  22. Ruiz-del Solar, J., Verschae, R.: Skin detection using neighborhood information. In: Sixth IEEE International Conference on Automatic Face and Gesture Recognition, pp. 463–468. IEEE (2004)

    Google Scholar 

  23. Soriano, M., Martinkauppi, B., Huovinen, S., Laaksonen, M.: Skin detection in video under changing illumination conditions. In: 15th International Conference on Pattern Recognition, vol. 1, pp. 839–842. IEEE (2000)

    Google Scholar 

  24. Subban, R., Mishra, R.: Human skin segmentation in color images using gaussian color model. In: Thampi, S.M., Abraham, A., Pal, S.K., Rodriguez, J.M.C. (eds.) Recent Advances in Intelligent Informatics. AISC, vol. 235, pp. 13–21. Springer, Heidelberg (2014)

    Chapter  Google Scholar 

  25. Vezhnevets, V., Sazonov, V., Andreeva, A.: A survey on pixel-based skin color detection techniques. In: Graphicon, vol. 3, pp. 85–92. Moscow, Russia (2003)

    Google Scholar 

  26. Wei, Y., Wen, F., Zhu, W., Sun, J.: Geodesic saliency using background priors. In: Fitzgibbon, A., Lazebnik, S., Perona, P., Sato, Y., Schmid, C. (eds.) ECCV 2012, Part III. LNCS, vol. 7574, pp. 29–42. Springer, Heidelberg (2012)

    Chapter  Google Scholar 

  27. Yang, C., Zhang, L., Lu, H., Ruan, X., Yang, M.H.: Saliency detection via graph-based manifold ranking. In: IEEE Conference on Computer Vision and Pattern Recognition, pp. 3166–3173. IEEE (2013)

    Google Scholar 

  28. Yang, M.H., Ahuja, N.: Gaussian mixture model for human skin color and its application in image and video databases. In: SPIE: Storage and Retrieval for Image and Video Databases VII, vol. 3656, pp. 458–466 (1999)

    Google Scholar 

  29. Zhu, Q., Wu, C.T., Cheng, K.T., Wu, Y.L.: An adaptive skin model and its application to objectionable image filtering. In: 12th annual ACM International Conference on Multimedia, pp. 56–63. ACM (2004)

    Google Scholar 

  30. Zhu, W., Liang, S., Wei, Y., Sun, J.: Saliency optimization from robust background detection. In: IEEE Conference on Computer Vision and Pattern Recognition, pp. 2814–2821. IEEE (2014)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Institute of Computing, University of Campinas, Campinas, SP, 13083-852, Brazil

    Anderson Santos & Helio Pedrini

Authors
  1. Anderson Santos
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Helio Pedrini
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Anderson Santos .

Editor information

Editors and Affiliations

  1. University of Malta, Msida, Malta

    George Azzopardi

  2. University of Groningen, Groningen, The Netherlands

    Nicolai Petkov

Rights and permissions

Reprints and permissions

Copyright information

© 2015 Springer International Publishing Switzerland

About this paper

Cite this paper

Santos, A., Pedrini, H. (2015). Human Skin Segmentation Improved by Saliency Detection. In: Azzopardi, G., Petkov, N. (eds) Computer Analysis of Images and Patterns. CAIP 2015. Lecture Notes in Computer Science(), vol 9257. Springer, Cham. https://doi.org/10.1007/978-3-319-23117-4_13

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-23117-4_13

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-23116-7

  • Online ISBN: 978-3-319-23117-4

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation