Skip to main content
Log in

Automatic detection and inpainting of specular reflections for colposcopic images

  • Research Article
  • Published:
Central European Journal of Computer Science

Abstract

Specular reflections are not wanted in images because they can really reduce the performance of image processing techniques. This is particularly true for medical images and especially for colposcopic images. There are several methods in the literature allowing to extract specular reflections, but only a few methods can perform an automatic extraction. In this paper, we propose a new method to extract and to restore specularities automatically. This method is based on Dichromatic Reflection Model (DRM) and multi-resolution inpainting technique (MIT). The DRM approach will retrieve specularities while the MIT technique re-establish colors in bright zones using local information. The proposed method achieves good results and does not need any a priori knowledge. The efficiency of this method for colposcopic images has been demonstrated through a collaboration with the oncology center of Marrakech University Hospital.

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

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  1. Armstrong E. P., Prophylaxis of Cervical Cancer and Related Cervical Disease: A Review of the Cost-Effectiveness of Vaccination Against Oncogenic HPV Types, J. Manag. Care. Pharm., 2010, 217–230

  2. Spencer J., Cervical Cancer (Deadly Diseases and Epidemics), First Edition, Chelsea House Publications, 2007

  3. Markovic N., Markovic O., What Every Woman Should Know about Cervical Cancer, First Edition, Springer, 2008

  4. Ferris D., Modern Colposcopy Textbook and Atlas, Second edition, Kendall Hunt Publishing Company, Dubuque, Iowa, 2002

    Google Scholar 

  5. Oh J., Hwang S., Lee J., Tavanapong W., Wong J., de Groen P. C., Informative Frame Classification for Endoscopy Video, Med. Image. Anal., 2007, 110–127

  6. Arnold M., Ghosh A., Ameling S., Lacey G., Automatic Segmentation and Inpainting of Specular Highlights for Endoscopic Imaging, EURASIP J. Iimage Video Process., 2010

  7. St Pierre C.A., Boisvert J., Grimard G., Cheriet F., Detection and Correction of Specular Reflections for Automatic Surgical Tool Segmentation in Thoracoscopic Images, Mach. Vision Appl., 2007, 22, 171–180

    Article  Google Scholar 

  8. Lange H., Automatic Glare Removal in Reflectance Imagery of the Uterine Cervix, In: SPIE Medical Imaging, (2005, San Diego, USA), SPIE, 2005, 240–250

  9. Zimmerman-Morene G., Greenspan H., Automatic Detection of Specular Reflections in Uterine Cervix Images, In: SPIE Medical Imaging, (February 2006, San Diego,USA), SPIE, 2006, 2037–2045

  10. Hervet E., Kardouchi M., Segmentation and Histogram Transform of Color Colposcopic Images, In: International Conference on Signal and Image Processing (ICISP), (June 2003, Agadir, Morocco), 2003, 412–420

  11. Shafer S.A., Using color to Separate Reflection Components, Color Research and Application, 1985, 210–218

  12. Agoston G.A., Color Theory and Its Application in Art and Design, Third Edition, Springer-Verlag, 1987

  13. Oliveira M., Bowen B., McKenna, R., Chang Y., Fast Digital Image Inpainting, In: International Conference on Visualization Imaging and Image Processing (VIIP), 2001, 261–266

  14. Shih T. K., Chang R. C, Digital Inpainting Survey and Multilayer Image Inpainting Algorithms, In: Information Technology and Applications (ICITA), (July 2005, Sydney, Australia), 2005, 15–24

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Othmane El Meslouhi.

About this article

Cite this article

El Meslouhi, O., Kardouchi, M., Allali, H. et al. Automatic detection and inpainting of specular reflections for colposcopic images. centr.eur.j.comp.sci. 1, 341–354 (2011). https://doi.org/10.2478/s13537-011-0020-2

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.2478/s13537-011-0020-2

Keywords

Navigation